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15/01/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
It starts with you - an engineer who cares about building data pipelines and models that deliver reliable, trusted data. You value data quality, clean transformations, and making data accessible to those who need it. Youll work alongside experienced engineers to build ETL/ELT pipelines, maintain dimensional models, and implement quality checks that turn raw data into actionable intelligence.
If you want to grow your skills building data products for mission-critical AI, join mission - this role is for you.
:Responsibilities
Build and maintain ETL/ELT pipelines using platform tooling - workflows that extract from sources, apply transformations, and load into analytical stores.
Develop and maintain data models - fact/dimension tables, aggregations, and views that serve analytics and ML use cases.
Implement data quality checks - validation rules, tests, and monitoring for data freshness and accuracy.
Maintain documentation and lineage - keeping data catalogs current and helping consumers understand data sources and transformations.
Work with stakeholders to understand data requirements and implement requested data products.
Troubleshoot pipeline failures - investigating issues, fixing bugs, and improving reliability.
Write clean, tested, well-documented SQL and Python code.
Collaborate with Data Platform on tooling needs; work with Datastores on database requirements; partner with ML, Data Science, Analytics, Engineering, and Product teams on data needs.
Design retrieval-friendly data artifacts - RAG-supporting views, feature tables, and embedding pipelines - with attention to freshness and governance expectations.
Requirements:
3+ years in data engineering, analytics engineering, BI development, or software engineering with strong SQL focus.
Strong SQL skills; complex queries, window functions, CTEs, query optimization basics
Data modeling - Understanding of dimensional modeling concepts; fact/dimension tables, star schemas
Transformation frameworks - Exposure to dbt, Spark SQL, or similar; understanding of modular, testable transformations
Orchestration - Familiarity with Airflow, Dagster, or similar; understanding of DAGs, scheduling, dependencies
Data quality - Awareness of data validation approaches, testing strategies, and quality monitoring
Python - Proficiency in Python for data manipulation and scripting; pandas, basic testing
Version control - Git workflows, code review practices, documentation
This position is open to all candidates.
 
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15/01/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
It starts with you - a technical leader whos passionate about data pipelines, data modeling, and growing high-performing teams. You care about data quality, business logic correctness, and delivering trusted data products to analysts, data scientists, and AI systems. Youll lead the Data Engineering team in building ETL/ELT pipelines, dimensional models, and quality frameworks that turn raw data into actionable intelligence.
If you want to lead a team that delivers the data products powering mission-critical AI systems, join mission - this role is for you.
:Responsibilities
Lead and grow the Data Engineering team - hiring, mentoring, and developing engineers while fostering a culture of ownership and data quality.
Define the data modeling strategy - dimensional models, data marts, and semantic layers that serve analytics, reporting, and ML use cases.
Own ETL/ELT pipeline development using platform tooling - orchestrated workflows that extract from sources, apply business logic, and load into analytical stores.
Drive data quality as a first-class concern - validation frameworks, testing, anomaly detection, and SLAs for data freshness and accuracy.
Establish lineage and documentation practices - ensuring consumers understand data origins, transformations, and trustworthiness.
Partner with stakeholders to understand data requirements and translate them into well-designed data products.
Build and maintain data contracts with consumers - clear interfaces, versioning, and change management.
Collaborate with Data Platform to define requirements for new platform capabilities; work with Datastores on database needs; partner with ML, Data Science, Analytics, Engineering, and Product teams to deliver trusted data.
Design retrieval-friendly data products - RAG-ready paths, feature tables, and embedding pipelines - while maintaining freshness and governance SLAs.
Requirements:
8+ years in data engineering, analytics engineering, or BI development, with 2+ years leading teams or technical functions. Hands-on experience building data pipelines and models at scale.
Data modeling - Dimensional modeling (Kimball), data vault, or similar; fact/dimension design, slowly changing dimensions, semantic layers
Transformation frameworks - dbt, Spark SQL, or similar; modular SQL, testing, documentation-as-code
Orchestration - Airflow, Dagster, or similar; DAG design, dependency management, scheduling, failure handling, backfills
Data quality - Great Expectations, dbt tests, Soda, or similar; validation rules, anomaly detection, freshness monitoring
Batch processing - Spark, SQL engines; large-scale transformations, optimization, partitioning strategies
Lineage & cataloging - DataHub, OpenMetadata, Atlan, or similar; metadata management, impact analysis, documentation
Messaging & CDC - Kafka, Debezium; event-driven ingestion, change data capture patterns
Languages - SQL (advanced), Python; testing practices, code quality, version control
This position is open to all candidates.
 
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3 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Responsibilities
Design, implement, and maintain robust data pipelines and ETL/ELT processes on GCP (BigQuery, Dataflow, Pub/Sub, etc.).
Build, orchestrate, and monitor workflows using Apache Airflow / Cloud Composer.
Develop scalable data models to support analytics, reporting, and operational workloads.
Apply software engineering best practices to data engineering: modular design, code reuse, testing, and version control.
Manage GCP resources (BigQuery reservations, Cloud Composer/Airflow DAGs, Cloud Storage, Dataplex, IAM).
Optimize data storage, query performance, and cost through partitioning, clustering, caching, and monitoring.
Collaborate with DevOps/DataOps to ensure data infrastructure is secure, reliable, and compliant.
Partner with analysts and data scientists to understand requirements and translate them into efficient data solutions.
Mentor junior engineers, provide code reviews, and promote engineering best practices.
Act as a subject matter expert for GCP data engineering tools and services.
Define and enforce standards for metadata, cataloging, and data documentation.
Implement monitoring and alerting for pipeline health, data freshness, and data quality.
Requirements:
Requirements:
Bachelors or Masters degree in Computer Science, Engineering, or related field.
6+ years of professional experience in data engineering or similar roles, with 3+ years of hands-on work in a cloud env, preferably on GCP.
Strong proficiency with BigQuery, Dataflow (Apache Beam), Pub/Sub, and Cloud Composer (Airflow).
Expert-level Python development skills, including object-oriented programming (OOP), testing, and code optimization.
Strong data modeling skills (dimensional modeling, star/snowflake schemas, normalized/denormalized designs).
Solid SQL expertise and experience with data warehousing concepts.
Familiarity with CI/CD, Terraform/Infrastructure as Code, and modern data observability tools.
Exposure to AI tools and methodologies (i.e, Vertex AI).
Strong problem-solving and analytical skills.
Ability to communicate complex technical concepts to non-technical stakeholders.
Experience working in agile, cross-functional teams.

Preferred Skills (Nice to Have):
Experience with Google Cloud Platform (GCP) .
Experience with Dataplex for data cataloging and governance.
Knowledge of streaming technologies (Kafka, Confluent).
Experience with Looker.
Cloud certifications (Google Professional Data Engineer, Google Cloud Architect).
This position is open to all candidates.
 
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21/01/2026
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.
 
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הגשת מועמדותהגש מועמדות
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
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 solutions-including 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:
6-10+ 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.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a talented Data Engineer to join our BI & Data team in Tel Aviv. You will play a pivotal role in building and optimizing the data infrastructure that powers our business. In this mid-level position, your primary focus will be on developing a robust single source of truth (SSOT) for revenue data, along with scalable data pipelines and reliable orchestration processes. If you are passionate about crafting efficient data solutions and ensuring data accuracy for decision-making, this role is for you.



Responsibilities:

Pipeline Development & Integration

- Design, build, and maintain robust data pipelines that aggregate data from various core systems into our data warehouse (BigQuery/Athena), with a special focus on our revenue Single Source of Truth (SSOT).

- Integrate new data sources (e.g. advertising platforms, content syndication feeds, financial systems) into the ETL/ELT workflow, ensuring seamless data flow and consolidation.

- Implement automated solutions for ingesting third-party data (leveraging tools like Rivery and scripts) to streamline data onboarding and reduce manual effort.

- Leverage AI-assisted development tools (e.g., Cursor, GitHub Copilot) to accelerate pipeline development

Optimization & Reliability

- Optimize ETL processes and SQL queries for performance and cost-efficiency - for example, refactoring and cleaning pipeline code to reduce runtime and cloud processing costs.

- Develop modular, reusable code frameworks and templates for common data tasks (e.g., ingestion patterns, error handling) to accelerate future development and minimize technical debt.

- Orchestrate and schedule data workflows to run reliably (e.g. consolidating daily jobs, setting up dependent task flows) so that critical datasets are refreshed on time.

- Monitor pipeline execution and data quality on a daily basis, quickly troubleshooting issues or data discrepancies to maintain high uptime and trust in the data.

Collaboration & Documentation

- Work closely with analysts and business stakeholders to understand data requirements and ensure the infrastructure meets evolving analytics needs (such as incorporating new revenue streams or content cost metrics into the SSOT).

- Document the data architecture, pipeline processes, and data schemas in a clear way so that the data ecosystem is well-understood across the team.

- Continuously research and recommend improvements or new technologies (e.g. leveraging AI tools for data mapping or anomaly detection) to enhance our data platforms capabilities and reliability and ensure our data ecosystem remains a competitive advantage.
Requirements:
4+ years of experience as a Data Engineer (or in a similar data infrastructure role), building and managing data pipelines at scale, with hands-on experience with workflow orchestration and scheduling (Cron, Airflow, or built-in scheduler tools)
Strong SQL skills and experience working with large-scale databases or data warehouses (ideally Google BigQuery or AWS Athena).
Solid understanding of data warehousing concepts, data modeling, and maintaining a single source of truth for enterprise data.
Demonstrated experience in data auditing and integrity testing, with ability to build 'trust-dashboards' or alerts that prove data reliability to executive stakeholders
Proficiency in a programming/scripting language (e.g. Python) for automating data tasks and building custom integrations.
This position is open to all candidates.
 
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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.
 
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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.
 
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29/01/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Our data engineering team is looking for an experienced professional with expertise in SQL, Python, and strong data modeling skills. In this role, you will be at the heart of our data ecosystem, designing and maintaining cross-engineering initiatives and projects, as well as developing high-quality data pipelines and models that drive decision-making across the organization.

You will play a key role in ensuring data quality, building scalable systems, and supporting cross-functional teams with clean, accurate, and actionable data.



What you will do:

Design, develop, and optimize data services and solutions required to support various company products (like FeatureStore or synthetic data management); Work closely with data analysts, data scientists, engineers, and cross-functional teams to understand data requirements and deliver high-quality solutions.
Design and integrate LLM- and agent-based capabilities into data platforms and services, enabling smarter data operations and AI-driven data products.
Design, develop, and optimize scalable data pipelines to ensure data is clean, accurate, and ready for analysis.
Build and maintain robust data models that support clinical, business intelligence, and operational needs.
Implement and enforce data quality standards, monitoring, and best practices across systems and pipelines.
Manage and optimize large-scale data storage and processing systems to ensure reliability and performance.
Requirements:
5+ years of experience as a Data Engineer / Backend Engineer (with strong emphasis on data processing)
Python Proficiency: Proven ability to build services, solutions, data pipelines, automations, and integration tools using Python.
SQL Expertise: Deep experience in crafting complex queries, optimizing performance, and working with large datasets.
Strong knowledge of data modeling principles and best practices for relational and dimensional data structures.
A passion for maintaining data quality and ensuring trust in business-critical data.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8523783
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דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
2 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We act as the central nervous system for engineering, enabling platform teams to unify their stack and expose it as a governed layer through golden paths for developers and AI agents.
By combining rich engineering context, workflows, and actions, we help organizations transition from manual processes to autonomous, AI-assisted engineering workflows while maintaining control and accountability.
As a product-led company, we believe in building world-class platforms that fundamentally shape how modern engineering organizations operate.
What youll do:
Lead the design and development of scalable and efficient data lake solutions that account for high-volume data coming from a large number of sources both pre-determined and custom.
Utilize advanced data modeling techniques to create robust data structures supporting reporting and analytics needs.
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into a data lake that will serve our company's users.
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency.
Collaborate with cross-functional teams (product, analytics, and R&D) to enhance our company's data solutions.
Who youll work with:
Youll be joining a collaborative and dynamic team of talented and experienced developers where creativity and innovation thrive.
You'll closely collaborate with our dedicated Product Managers and Designers, working hand in hand to bring our developer portal product to life.
Additionally, you will have the opportunity to work closely with our customers and engage with our product community. Your insights and interactions with them will play an important role to ensure we deliver the best product possible.
Together, we'll continue to empower platform engineers and developers worldwide, providing them with the tools they need to create seamless and robust developer portals. Join us in our mission to revolutionize the developer experience!
Requirements:
5+ years of experience in a Data Engineering role
Expertise in building scalable pipelines and ETL/ELT processes, with proven experience with data modeling
Expert-level proficiency in SQL and experience with large-scale datasets
Strong experience with Snowflake
Strong experience with cloud data platforms and storage solutions such as AWS S3, or Redshift
Hands-on experience with ETL/ELT tools and orchestration frameworks such as Apache Airflow and dbt
Experience with Python and software development
Strong analytical and storytelling capabilities, with a proven ability to translate data into actionable insights for business users
Collaborative mindset with experience working cross-functionally with data engineers and product managers
Excellent communication and documentation skills, including the ability to write clear data definitions, dashboard guides, and metric logic
Advantages:
Experience in NodeJs + Typescript
Experience with streaming data technologies such as Kafka or Kinesis
Familiarity with containerization tools such as Docker and Kubernetes
Knowledge of data governance and data security practices.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8533929
סגור
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סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
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.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8482840
סגור
שירות זה פתוח ללקוחות VIP בלבד