Senior Solutions Engineer - Big Data & Data Infrastructure

לפני 3 שעות

Senior Solutions Engineer - Big Data & Data Infrastructure

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

Requirements:
2-4 years in software / solution or infrastructure engineering, with 2-4 years focused on building / maintaining large-scale data pipelines / storage & database solutions.
Proficiency in Trino, Spark (Structured Streaming & batch) and solid working knowledge of Apache Kafka.
Coding background in Python (must-have); familiarity with Bash and scripting tools is a plus.
Deep understanding of data storage architectures including SQL, NoSQL, and HDFS.
Solid grasp of DevOps practices, including containerization (Docker), orchestration (Kubernetes), and infrastructure provisioning (Terraform).
Experience with distributed systems, stream processing, and event-driven architecture.
Hands-on familiarity with benchmarking and performance profiling for storage systems, databases, and analytics engines.
Excellent communication skills-youll be expected to explain your thinking clearly, guide customer conversations, and collaborate across engineering and product teams.

This position is open to all candidates.

Hide

עדכון קורות החיים לפני שליחה

8512434

שירות זה פתוח ללקוחות VIP בלבד

משרות דומות שיכולות לעניין אותך

דיווח על תוכן לא הולם או מפלה

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

17/12/2025

Senior Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from an HPE office.
Job Description:
We are looking for a highly skilled Senior Data Engineer with strong architectural expertise to design and evolve our next-generation data platform. You will define the technical vision, build scalable and reliable data systems, and guide the long-term architecture that powers analytics, operational decision-making, and data-driven products across the organization.
This role is both strategic and hands-on. You will evaluate modern data technologies, define engineering best practices, and lead the implementation of robust, high-performance data solutionsincluding the design, build, and lifecycle management of data pipelines that support batch, streaming, and near-real-time workloads.
What Youll Do
Architecture & Strategy
Own the architecture of our data platform, ensuring scalability, performance, reliability, and security.
Define standards and best practices for data modeling, transformation, orchestration, governance, and lifecycle management.
Evaluate and integrate modern data technologies and frameworks that align with our long-term platform strategy.
Collaborate with engineering and product leadership to shape the technical roadmap.
Engineering & Delivery
Design, build, and manage scalable, resilient data pipelines for batch, streaming, and event-driven workloads.
Develop clean, high-quality data models and schemas to support analytics, BI, operational systems, and ML workflows.
Implement data quality, lineage, observability, and automated testing frameworks.
Build ingestion patterns for APIs, event streams, files, and third-party data sources.
Optimize compute, storage, and transformation layers for performance and cost efficiency.
Leadership & Collaboration
Serve as a senior technical leader and mentor within the data engineering team.
Lead architecture reviews, design discussions, and cross-team engineering initiatives.
Work closely with analysts, data scientists, software engineers, and product owners to define and deliver data solutions.
Communicate architectural decisions and trade-offs to technical and non-technical stakeholders.

Requirements:
610+ years of experience in Data Engineering, with demonstrated architectural ownership.
Expert-level experience with Snowflake (mandatory), including performance optimization, data modeling, security, and ecosystem components.
Expert proficiency in SQL and strong Python skills for pipeline development and automation.
Experience with modern orchestration tools (Airflow, Dagster, Prefect, or equivalent).
Strong understanding of ELT/ETL patterns, distributed processing, and data lifecycle management.
Familiarity with streaming/event technologies (Kafka, Kinesis, Pub/Sub, etc.).
Experience implementing data quality, observability, and lineage solutions.
Solid understanding of cloud infrastructure (AWS, GCP, or Azure).
Strong background in DataOps practices: CI/CD, testing, version control, automation.
Proven leadership in driving architectural direction and mentoring engineering teams
Nice to Have
Experience with data governance or metadata management tools.
Hands-on experience with DBT, including modeling, testing, documentation, and advanced features.
Exposure to machine learning pipelines, feature stores, or MLOps.
Experience with Terraform, CloudFormation, or other IaC tools.
Background designing systems for high scale, security, or regulated environments.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8461496

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

01/01/2026

Staff Data Engineer, Group Tech Lead

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Were looking for an experienced and passionate Staff Data Engineer to join our Data Platform group in TLV as a Tech Lead. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of our companys data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives our company toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
In this role youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across our company to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization.

Requirements:
8+ years of experience in data-related roles such as Data Engineer, Data Infrastructure Engineer, BI Engineer, or Machine Learning Platform Engineer, with significant experience in at least two of these areas
A B.Sc. in Computer Science or a related technical field (or equivalent experience)
Extensive expertise in designing and implementing Data Lakes and Data Warehouses, including strong skills in data modeling and building scalable storage solutions
Proven experience in building large-scale data infrastructures, including both batch processing and streaming pipelines
A deep understanding of Machine Learning infrastructure, including tools and frameworks that enable Data Scientists to efficiently develop, deploy, and maintain models in production, an advantage
Proficiency in Python, Pulumi/Terraform, Apache Spark, AWS, Kubernetes (K8s), and Kafka for building scalable, reliable, and high-performing data solutions
Strong knowledge of databases, including SQL (schema design, query optimization) and NoSQL, with a solid understanding of their use cases
Ability to work in an office environment a minimum of 3 days a week
Enthusiasm about learning and adapting to the exciting world of AI - a commitment to exploring this field is a fundamental part of our culture.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8482879

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

23/12/2025

Senior Data Platform Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a Senior Data Platform Engineer to design, build, and scale next-generation data platform, the backbone powering our AI-driven insights.
This role sits at the intersection of data engineering, infrastructure, and MLOps, owning the architecture and reliability of our data ecosystem end-to-end.
Youll work closely with data scientists,r&d teams, analysts to create a robust platform that supports varying use cases, complex ingestion, and AI-powered analytics.
Responsibilities:
Architect and evolve a scalable, cloud-native data platform that supports batch, streaming, analytics, and AI/LLM workloads across R&D.
Help define and implement standards for how data is modeled, stored, governed, and accessed
Design and build data lakes and data warehouses
Develop and maintain complex, reliable, and observable data pipelines
Implement data quality, validation, and monitoring frameworks
Collaborate with ML and data science teams to connect AI/LLM workloads to production data pipelines, enabling RAG, embeddings, and feature engineering flows.
Manage and optimize relational and non-relational datastores (Postgres, Elasticsearch, vector DBs, graph DBs).
Build internal tools and self-service capabilities that enable teams to easily ingest, transform, and consume data.
Contribute to data observability, governance, documentation, and platform visibility
Drive strong engineering practices
Evaluate and integrate emerging technologies that enhance scalability, reliability, and AI integration in the platform.

Requirements:
7+ years experience building/operating data platforms
Strong Python programming skills
Proven experience with cloud data lakes and warehouses (Databricks, Snowflake, or equivalent).
Data orchestration experience (Airflow)
Solid understanding of AWS services
Proficiency with relational databases and search/analytics stores
Experience designing complex data pipelines, managing data quality, lineage, and observability in production.
Familiarity with CI/CD, GitOps, and IaC
Excellent understanding of distributed systems, data partitioning, and schema evolution.
Strong communication skills, ability to document and present technical designs clearly.
Advantages:
Experience with vector databases and graph databases
Experience integrating AI/LLM workloads into data pipelines (feature stores, retrieval pipelines, embeddings).
Familiarity with event streaming and CDC patterns.
Experience with data catalog, lineage, or governance tools
Knowledge of monitoring and alerting stacks
Hands-on experience with multi-source data product architectures.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8470086

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

12/01/2026

Senior Data Engineer I - GenAI Foundation Models

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Required Senior Data Engineer I - GenAI Foundation Models
21679
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

דרישות:
Bachelors or masters degree in computer science, Engineering, Statistics, or a related field.
Minimum of 6 years of experience as a Data Engineer or a similar role, with a consistent record of successfully delivering ML/Data solutions.
You have built production data pipelines in the cloud, setting up data-lake and server-less solutions; ‌ you have hands-on experience with schema design and data modeling and working with ML scientists and ML engineers to provide production level ML solutions.
You have experience designing systems E2E and knowledge of basic concepts (lb, db, caching, NoSQL, etc)
Strong programming skills in languages such as Python and Java.
Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.
Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.
Experience with Data Warehousing and ETL/ELT pipelines
Experience in data processing for large-scale language models like GPT, BERT, or similar architectures - an advantage.
Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and המשרה מיועדת לנשים ולגברים כאחד.

עדכון קורות החיים לפני שליחה

8498339

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

6 ימים

Senior Data Platform Engineer - Applied AI Engineering Group

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

It starts with you - an engineer driven to build modern, real-time data platforms that help teams move faster with trust. You care about great service, performance, and cost. Youll architect and ship a top-of-the-line open streaming data lake/lakehouse and data stack, turning massive threat signals into intuitive, self-serve data and fast retrieval for humans and AI agents - powering a unified foundation for AI-driven mission-critical workflows across cloud and on-prem.
If you want to make a meaningful impact, join mission and build best-in-class data systems that move the world forward - this role is for you.
:Responsibilities
Build self-serve platform surfaces (APIs, specs, CLI/UI) for streaming and batch pipelines with correctness, safe replay/backfills, and CDC.
Run the open data lake/lakehouse across cloud and on-prem; enable schema evolution and time travel; tune partitioning and compaction to balance latency, freshness, and cost.
Provide serving and storage across real-time OLAP, OLTP, document engines, and vector databases.
Own the data layer for AI - trusted datasets for training and inference, feature and embedding storage, RAG-ready collections, and foundational building blocks that accelerate AI development across the organization.
Enable AI-native capabilities - support agentic pipelines, self-tuning processes, and secure sandboxing for model experimentation and deployment.
Make catalog, lineage, observability, and governance first-class - with clear ownership, freshness SLAs, and access controls.
Improve performance and cost by tuning runtimes and I/O, profiling bottlenecks, planning capacity, and keeping spend predictable.
Ship paved-road tooling - shared libraries, templates, CI/CD, IaC, and runbooks - while collaborating across AI, ML, Data Science, Engineering, Product, and DevOps. Own architecture, documentation, and operations end-to-end.

Requirements:
6+ years in software engineering, data engineering, platform engineering, or distributed systems, with hands-on experience building and operating data infrastructure at scale.
Streaming & ingestion - Technologies like Flink, Structured Streaming, Kafka, Debezium, Spark, dbt, Airflow/Dagster
Open data lake/lakehouse - Table formats like Iceberg, Delta, or Hudi; columnar formats; partitioning, compaction, schema evolution, time-travel
Serving & retrieval - OLAP engines like ClickHouse or Trino; vector databases like Milvus, Qdrant, or LanceDB; low-latency stores like Redis, ScyllaDB, or DynamoDB
Databases - OLTP systems like Postgres or MySQL; document/search engines like MongoDB or ElasticSearch; serialization with Avro/Protobuf; warehouse patterns
Platform & infra - Kubernetes, AWS, Terraform or similar IaC, CI/CD, observability, incident response
Performance & cost - JVM tuning, query optimization, capacity planning, compute/storage cost modeling
Engineering craft - Java/Scala/Python, testing, secure coding, AI coding tools like Cursor, Claude Code, or Copilot

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8504233

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

12/01/2026

Data Engineer II - GenAI

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Required Data Engineer II - GenAI
20718
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
As a Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

דרישות:
Bachelors or masters degree in computer science, Engineering, Statistics, or a related field.
Minimum of 3 years of experience as a Data Engineer or a similar role, with a consistent record of successfully delivering ML/Data solutions.
You have built production data pipelines in the cloud, setting up data-lake and server-less solutions; ‌ you have hands-on experience with schema design and data modeling and working with ML scientists and ML engineers to provide production level ML solutions.
You have experience designing systems E2E and knowledge of basic concepts (lb, db, caching, NoSQL, etc)
Strong programming skills in languages such as Python and Java.
Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.
Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.
Experience with Data Warehousing and ETL/ELT pipelines
Experience in data processing for large-scale language models like GPT, BERT, or similar architectures - an advantage.
Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib - an advantage.#ENG המשרה מיועדת לנשים ולגברים כאחד.

עדכון קורות החיים לפני שליחה

8498343

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

1 ימים

Senior Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Required Senior Data Engineer
About us:
A pioneering health-tech startup on a mission to revolutionize weight loss and well-being. Our innovative metabolic measurement device provides users with a comprehensive understanding of their metabolism, empowering them with personalized, data-driven insights to make informed lifestyle choices.
Data is at the core of everything we do. We collect and analyze vast amounts of user data from our device and app to provide personalized recommendations, enhance our product, and drive advancements in metabolic health research. As we continue to scale, our data infrastructure is crucial to our success and our ability to empower our users.
About the Role:
As a Senior Data Engineer, youll be more than just a coder - youll be the architect of our data ecosystem. Were looking for someone who can design scalable, future-proof data pipelines and connect the dots between DevOps, backend engineers, data scientists, and analysts.
Youll lead the design, build, and optimization of our data infrastructure, from real-time ingestion to supporting machine learning operations. Every choice you make will be data-driven and cost-conscious, ensuring efficiency and impact across the company.
Beyond engineering, youll be a strategic partner and problem-solver, sometimes diving into advanced analysis or data science tasks. Your work will directly shape how we deliver innovative solutions and support our growth at scale.
Responsibilities:
Design and Build Data Pipelines: Architect, build, and maintain our end-to-end data pipeline infrastructure to ensure it is scalable, reliable, and efficient.
Optimize Data Infrastructure: Manage and improve the performance and cost-effectiveness of our data systems, with a specific focus on optimizing pipelines and usage within our Snowflake data warehouse. This includes implementing FinOps best practices to monitor, analyze, and control our data-related cloud costs.
Enable Machine Learning Operations (MLOps): Develop the foundational infrastructure to streamline the deployment, management, and monitoring of our machine learning models.
Support Data Quality: Optimize ETL processes to handle large volumes of data while ensuring data quality and integrity across all our data sources.
Collaborate and Support: Work closely with data analysts and data scientists to support complex analysis, build robust data models, and contribute to the development of data governance policies.

Requirements:
Bachelor's degree in Computer Science, Engineering, or a related field.
Experience: 5+ years of hands-on experience as a Data Engineer or in a similar role.
Data Expertise: Strong understanding of data warehousing concepts, including a deep familiarity with Snowflake.
Technical Skills:
Proficiency in Python and SQL.
Hands-on experience with workflow orchestration tools like Airflow.
Experience with real-time data streaming technologies like Kafka.
Familiarity with container orchestration using Kubernetes (K8s) and dependency management with Poetry.
Cloud Infrastructure: Proven experience with AWS cloud services (e.g., EC2, S3, RDS).

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8510072

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

31/12/2025

Data Infrastructure Engineer

חברה חסויה

Location: Tel Aviv-Yafo and Binyamina-Giv'at Ada

Job Type: Full Time

We use cutting-edge innovations in financial technology to bring leading data and features that allow individuals to be qualified instantly, making purchases at the point-of-sale fast, fair and easy for consumers from all walks of life.
As part of our Data Engineering team, you will not only build scalable data platforms but also directly enable portfolio growth by supporting new funding capabilities, loan sales and securitization, and improving cost efficiency through automated and trusted data flows that evolve our accounting processes.
Responsibilities
Design and build data solutions that support our companys core business goals, from enabling capital market transactions (loan sales and securitization) to providing
reliable insights for reducing the cost of capital.
Develop advanced data pipelines and analytics to support finance, accounting, and product growth initiatives.
Create ELT processes and SQL queries to bring data to the data warehouse and other data sources.
Develop data-driven finance products that accelerate funding capabilities and automate accounting reconciliations.
Own and evolve data lake pipelines, maintenance, schema management, and improvements.
Create new features from scratch, enhance existing features, and optimize existing functionality.
Collaborate with stakeholders across Finance, Product, Backend Engineering, and Data Science to align technical work with business outcomes.
Implement new tools and modern development approaches that improve both scalability and business agility.
Ensure adherence to coding best practices and development of reusable code.
Constantly monitor the data platform and make recommendations to enhance architecture, performance, and cost efficiency.

Requirements:
4+ years of experience as a Data Engineer.
4+ years of Python and SQL experience.
4+ years of direct experience with SQL (Redshift/Snowflake), data modeling, data warehousing, and building ELT/ETL pipelines (DBT & Airflow preferred).
3+ years of experience in scalable data architecture, fault-tolerant ETL, and data quality monitoring in the cloud.
Hands-on experience with cloud environments (AWS preferred) and big data technologies (EMR, EC2, S3, Snowflake, Spark Streaming, Kafka, DBT).
Strong troubleshooting and debugging skills in large-scale systems.
Deep understanding of distributed data processing and tools such as Kafka, Spark, and Airflow.
Experience with design patterns, coding best practices, and data modeling.
Proficiency with Git and modern source control.
Basic Linux/Unix system administration skills.
Nice to Have
Familiarity with fintech business processes (funding, securitization, loan servicing, accounting).- Huge advantage
BS/MS in Computer Science or related field.
Experience with NoSQL or large-scale DBs.
DevOps experience in AWS.
Microservices experience.
2+ years of experience in Spark and the broader Data Engineering ecosystem.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8481603

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

01/01/2026

Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for an experienced and visionary Data Platform Engineer to help design, build and scale our BI platform from the ground up.
In this role, you will be responsible for building the foundations of our data analytics platform - enabling scalable data pipelines and robust data modeling to support real-time and batch analytics, ML models and business insights that serve both business intelligence and product needs.
You will be part of the R&D team, collaborating closely with engineers, analysts, and product managers to deliver a modern data architecture that supports internal dashboards and future-facing operational analytics.
If you enjoy architecting from scratch, turning raw data into powerful insights, and owning the full data lifecycle - this role is for you!
Responsibilities
Take full ownership of the design and implementation of a scalable and efficient BI data infrastructure, ensuring high performance, reliability and security.
Lead the design and architecture of the data platform - from integration to transformation, modeling, storage, and access.
Build and maintain ETL/ELT pipelines, batch and real-time, to support analytics, reporting, and product integrations.
Establish and enforce best practices for data quality, lineage, observability, and governance to ensure accuracy and consistency.
Integrate modern tools and frameworks such as Airflow, dbt, Databricks, Power BI, and streaming platforms.
Collaborate cross-functionally with product, engineering, and analytics teams to translate business needs into data infrastructure.
Promote a data-driven culture - be an advocate for data-driven decision-making across the company by empowering stakeholders with reliable and self-service data access.

Requirements:
5+ years of hands-on experience in data engineering and in building data products for analytics and business intelligence.
Strong hands-on experience with ETL orchestration tools (Apache Airflow), and data lakehouses (e.g., Snowflake/BigQuery/Databricks)
Vast knowledge in both batch processing and streaming processing (e.g., Kafka, Spark Streaming).
Proficiency in Python, SQL, and cloud data engineering environments (AWS, Azure, or GCP).
Familiarity with data visualization tools ( Power BI, Looker, or similar.
BSc in Computer Science or a related field from a leading university
Nice to have
Experience working in early-stage projects, building data systems from scratch.
Background in building operational analytics pipelines, in which analytical data feeds real-time product business logic.
Hands-on experience with ML model training pipelines.
Experience in cost optimization in modern cloud environments.
Knowledge of data governance principles, compliance, and security best practices.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8482840

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

לפני 7 שעות

Senior Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Your Mission As a Senior Data Engineer, your mission is to build the scalable, reliable data foundation that empowers us to make data-driven decisions. You will serve as a bridge between complex business needs and technical implementation, translating raw data into high-value assets. You will own the entire data lifecycle-from ingestion to insight-ensuring that our analytics infrastructure scales as fast as our business.

Key Responsibilities:
Strategic Data Modeling: Translate complex business requirements into efficient, scalable data models and schemas. You will design the logic that turns raw events into actionable business intelligence.
Pipeline Architecture: Design, implement, and maintain resilient data pipelines that serve multiple business domains. You will ensure data flows reliably, securely, and with low latency across our ecosystem.
End-to-End Ownership: Own the data development lifecycle completely-from architectural design and testing to deployment, maintenance, and observability.
Cross-Functional Partnership: Partner closely with Data Analysts, Data Scientists, and Software Engineers to deliver end-to-end data solutions.

Requirements:
What You Bring:
Your Mindset:
Data as a Product: You treat data pipelines and tables with the same rigor as production APIs-reliability, versioning, and uptime matter to you.
Business Acumen: You dont just move data; you understand the business questions behind the query and design solutions that provide answers.
Builders Spirit: You work independently to balance functional needs with non-functional requirements (scale, cost, performance).
Your Experience & Qualifications:
Must Haves:
6+ years of experience as a Data Engineer, BI Developer, or similar role.
Modern Data Stack: Strong hands-on experience with DBT, Snowflake, Databricks, and orchestration tools like Airflow.
SQL & Modeling: Strong proficiency in SQL and deep understanding of data warehousing concepts (Star schema, Snowflake schema).
Data Modeling: Proven experience in data modeling and business logic design for complex domains-building models that are efficient and maintainable.
Modern Workflow: Proven experience leveraging AI assistants to accelerate data engineering tasks.
Bachelors degree in Computer Science, Industrial Engineering, Mathematics, or an equivalent analytical discipline.
Preferred / Bonus:
Cloud Data Warehouses: Experience with BigQuery or Redshift.
Coding Skills: Proficiency in Python for data processing and automation.
Big Data Tech: Familiarity with Spark, Kubernetes, Docker.
BI Integration: Experience serving data to BI tools such as Looker, Tableau, or Superset.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8511741

שירות זה פתוח ללקוחות VIP בלבד