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Location: Merkaz
Job Type: Full Time
abra professional services is seeking for an senior data engineer. We are seeking a Senior Data Engineer to lead the technical development of our Data Fabric within a military program. This role involves technical leadership in building contextual data pipelines, working with big data lakehouse architectures, and driving data pipeline automation.
Requirements:
MUST HAVE Requirements: 5+ years of hands-on experience as a Big Data Engineer
* Proven ability to design and deploy Big Data & AI solutions using frameworks and tools such as:
* Apache NiFi
* Kafka
* Spark
* Graph DB
* NoSQL databases Strong coding proficiency in Python and Bash
* Experience building large-scale data pipelines for data processing, transformation, and analytics
* Ability to define and manage metadata schemas
* Experience developing data workflows (e.g., metadata generation, auto-extraction, validation, format conversion)
* Experience developing tools for data observability and compliance analytics
* Ability to analyze and report on complex datasets and results
* Experience working with big data lakehouse architectures
* Ability to explore, enhance, and manage data fusion from multiple data sources
* Experience developing analytics tools, algorithms, and programs
* Technical leadership of data structure design for contextual pipelines
* Collaboration experience with Data Scientists and Architects
* Strong ability to work independently, learn new technologies, and apply innovative solutions
* Excellent interpersonal skills and ability to work as part of a team MSc in Computer Science or Data Science Advantages:
* Experience with managing metadata and taxonomy concepts alongside big data objects
* Experience working with public cloud Big Data & AI services
* Familiarity with machine learning concepts
* Strong technical skills
* Independent, hands-on developer
* Curious, open-minded, fast learner, and a strong team player
This position is open to all candidates.
 
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18/12/2025
חברה חסויה
Job Type: Full Time
We're in search of an experienced and skilled Senior Data Engineer to join our growing data team. As part of our data team, you'll be at the forefront of crafting a groundbreaking solution that leverages cutting-edge technology to combat fraud. The ideal candidate will have a strong background in designing and implementing large-scale data solutions, with the potential to grow into a leadership role. This position requires a deep understanding of modern data architectures, cloud technologies, and the ability to drive technical initiatives that align with business objectives.
Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud.
Your Arena
Design, develop, and maintain scalable, robust data pipelines and ETL processes
Architect and implement complex data models across various storage solutions
Collaborate with R&D teams, data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality solutions
Ensure data quality, consistency, security, and compliance across all data systems
Play a key role in defining and implementing data strategies that drive business value
Contribute to the continuous improvement of our data architecture and processes
Champion and implement data engineering best practices across the R&D organization, serving as a technical expert and go-to resource for data-related questions and challenges
Participate in and sometimes lead code reviews to maintain high coding standards
Troubleshoot and resolve complex data-related issues in production environments
Evaluate and recommend new technologies and methodologies to improve our data infrastructure.
Requirements:
What It Takes - Must haves::
5+ years of experience in data engineering, with specific, strong proficiency in Python & software engineering principles - Must
Extensive experience with AWS, GCP, Azure and cloud-native architectures - Must
Deep knowledge of both relational (e.g., PostgreSQL) and NoSQL databases - Must
Designing and implementing data warehouses and data lakes - Must
Strong understanding of data modeling techniques - Must
Expertise in data manipulation libraries (e.g., Pandas) and big data processing frameworks - Must
Experience with data validation tools such as Pydantic & Great Expectations - Must
Proficiency in writing and maintaining unit tests (e.g., Pytest) and integration tests - Must
Nice-to-Haves:
Apache Iceberg - Experience building, managing and maintaining Iceberg lakehouse architecture with S3 storage and AWS Glue catalog - Strong Advantage
Apache Spark - Proficiency in optimizing Spark jobs, understanding partitioning strategies, and leveraging core framework capabilities for large-scale data processing - Strong Advantage
Modern data stack tools - DBT, DuckDB, Dagster or any other Data orchestration tool (e.g., Apache Airflow, Prefect) - Advantage
Designing and developing backend systems, including- RESTful API design and implementation, microservices architecture, event-driven systems, RabbitMQ, Apache Kafka - Advantage
Containerization technologies- Docker, Kubernetes, and IaC (e.g., Terraform) - Advantage
Stream processing technologies (e.g., Apache Kafka, Apache Flink) - Advantage
Understanding of compliance requirements (e.g., GDPR, CCPA) - Advantage
Experience mentoring junior engineers or leading small project teams
Excellent communication skills with the ability to explain complex technical concepts to various audiences
Demonstrated ability to work independently and lead technical initiatives
Relevant certifications in cloud platforms or data technologies.
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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חברה חסויה
Location: Rosh Haayin
Job Type: Full Time
The ideal candidate is not afraid of data in any form or scale, and is experienced with cloud services to ingest, stream, store, and manipulate data. The Data Engineer will support new system designs and migrate existing ones, working closely with solutions architects, project managers, and data scientists. The candidate must be self-directed, a fast learner, and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing or re-designing our customers data architecture to support their next generation of products, data initiatives, and machine learning systems.





Summary of Key Responsibilities



To meet compliance and regulatory requirements, keep our customers data separated and secure.
Design, Build, and operate the infrastructure required for optimal data extraction, transformation, and loading from a wide variety of data sources using SQL, cloud migration tools, and big data technologies.
Optimize various RDBMS engines in the cloud and solve customers' security, performance, and operational problems.
Design, build, and operate large, complex data lakes that meet functional / non-functional business requirements.
Optimize various data types' ingestion, storage, processing, and retrieval, from near real-time events and IoT to unstructured data such as images, audio, video, documents, and in between.
Work with customers' and internal stakeholders including the Executive, Product, Data, Software Development and Design teams to assist with data-related technical issues and support their data infrastructure and business needs.
Requirements:
5+ years of experience in a Data Engineer role in a cloud native ecosystem.
3+ years of experience in AWS Data Services (mandatory)
Bachelor's (Graduate preferred) degree in Computer Science, Mathematics, Informatics, Information Systems or another quantitative field.
Working experience with the following technologies/tools:
big data tools: Spark, ElasticSearch, Kafka, Kinesis etc.
Relational SQL and NoSQL databases, such as MySQL or Postgres and DynamoDB or Cassandra.
Functional and scripting languages: Python, Java, Scala, etc.
Advanced SQL
Experience building and optimizing big data pipelines, architectures and data sets.
Working knowledge of message queuing, stream processing, and highly scalable big data stores.
Experience supporting and working with external customers in a dynamic environment.
Articulate with great communication and presentation skills
Team player who can train as well as learn from others.
Fluency in Hebrew and English is essential
This position is open to all candidates.
 
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Location: Jerusalem
Job Type: Full Time and Temporary
We are seeking a skilled and motivated Data Engineer to join our dynamic team. The ideal candidate will have extensive experience in building and optimizing data pipelines, handling large datasets, and working within cloud-based and on-premise environments.
You will be responsible for designing and implementing efficient, scalable solutions to manage, process, and analyze high volumes of data, ensuring the reliability and performance of our data infrastructure.
What will your job look like:
Design, build, and maintain scalable data pipelines to process large datasets efficiently
Develop and implement data models and architectures that support both real-time and batch data processing
Ensure data integrity, security, and accuracy across all systems
Collaborate with data scientists, analysts, and other engineers to ensure data availability and quality
Optimize data retrieval and storage processes to handle large volumes of data seamlessly
Work with structured, semi-structured, and unstructured data, integrating various data sources
Troubleshoot and resolve data issues, ensuring continuous operation of the data infrastructure
Maintain and enhance ETL processes, ensuring scalability and performance in handling large datasets
Stay up-to-date with industry best practices and emerging technologies related to big data engineering
Requirements:
Bachelors degree in Computer Science, Engineering, or a related field
At least 4 years experience in data engineering, with a focus on large-scale data processing and big data technologies
Strong proficiency in Python
Experience with data pipeline and workflow management tools
Hands-on experience with large-scale data processing frameworks like Apache Spark, Hadoop, or similar
Familiarity with data modeling, ETL processes, and data warehousing concepts like Table formats. Apache Iceberg, or similar
Good knowledge of relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., Cassandra, MongoDB)
Experience with AWS-based data lakes, including working with Amazon S3 for storage, querying data using Amazon Athena, and managing datasets stored in Parquet format
Significant ownership ability
Nice to have:
Knowledge of machine learning frameworks and integrating data pipelines for model training and deployment
Experience with version control systems (e.g., Git), CI/CD pipelines, and automation tools
Experience with containerization (Docker, Kubernetes)
This position is open to all candidates.
 
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
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.
 
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19/12/2025
Job Type: Full Time
Welcome to Chargeflow Chargeflow is at the forefront of fintech + AI innovation, backed by leading venture capital firms. Our mission is to build a fraud-free global commerce ecosystem by leveraging the newest technology, freeing online businesses to focus on their core ideas and growth. We are building the future, and we need you to help shape it. Who We're Looking For - The Dream Maker We're in search of an experienced and skilled Senior Data Engineer to join our growing data team. As part of our data team, you'll be at the forefront of crafting a groundbreaking solution that leverages cutting-edge technology to combat fraud. The ideal candidate will have a strong background in designing and implementing large-scale data solutions, with the potential to grow into a leadership role. This position requires a deep understanding of modern data architectures, cloud technologies, and the ability to drive technical initiatives that align with business objectives. Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud. Your Arena
* Design, develop, and maintain scalable, robust data pipelines and ETL processes
* Architect and implement complex data models across various storage solutions
* Collaborate with R&D teams, data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality solutions
* Ensure data quality, consistency, security, and compliance across all data systems
* Play a key role in defining and implementing data strategies that drive business value
* Contribute to the continuous improvement of our data architecture and processes
* Champion and implement data engineering best practices across the R&D organization, serving as a technical expert and go-to resource for data-related questions and challenges
* Participate in and sometimes lead code reviews to maintain high coding standards
* Troubleshoot and resolve complex data-related issues in production environments
* Evaluate and recommend new technologies and methodologies to improve our data infrastructure
Requirements:
What It Takes - Must haves: 5+ years of experience in data engineering, with specific, strong proficiency in Python & software engineering principles - Must
* Extensive experience with GraphDB - MUST
* Extensive experience with AWS, GCP, Azure and cloud-native architectures - Must
* Deep knowledge of both relational (e.g., PostgreSQL) and NoSQL databases - Must
* Designing and implementing data warehouses and data lakes - Must
* Strong understanding of data modeling techniques - Must
* Expertise in data manipulation libraries (e.g., Pandas) and big data processing frameworks - Must
* Experience with data validation tools such as Pydantic & Great Expectations - Must
* Proficiency in writing and maintaining unit tests (e.g., Pytest) and integration tests - Must Nice-to-Haves
* Apache Iceberg - Experience building, managing and maintaining Iceberg lakehouse architecture with S3 storage and AWS Glue catalog - Strong Advantage
* Apache Spark - Proficiency in optimizing Spark jobs, understanding partitioning strategies, and leveraging core framework capabilities for large-scale data processing - Strong Advantage
* Modern data stack tools - DBT, DuckDB, Dagster or any other Data orchestration tool (e.g., Apache Airflow, Prefect) - Advantage
* Designing and developing backend systems, including- RESTful API design and implementation, microservices architecture, event-driven systems, RabbitMQ, Apache Kafka - Advantage
* Containerization technologies- Docker, Kubernetes, and IaC (e.g., Terraform) - Advantage
* Stream processing technologies (e.g., Apache Kafka, Apache Flink) - Advantage
* Understanding of compliance requirements (e.g., GDPR, CCPA) - A
This position is open to all candidates.
 
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24/12/2025
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a Big Data Engineer to develop and integrate systems that retrieve, process and analyze data from around the digital world, generating customer-facing data. This role will report to our Team Manager, R&D.
Why is this role so important?
We are a data-focused company, and data is the heart of our business.
As a big data engineer developer, you will work at the very core of the company, designing and implementing complex high scale systems to retrieve and analyze data from millions of digital users.
Your role as a big data engineer will give you the opportunity to use the most cutting-edge technologies and best practices to solve complex technical problems while demonstrating technical leadership.
So, what will you be doing all day?
Your role as part of the R&D team means your daily responsibilities may include:
Design and implement complex high scale systems using a large variety of technologies.
You will work in a data research team alongside other data engineers, data scientists and data analysts. Together you will tackle complex data challenges and bring new solutions and algorithms to production.
Contribute and improve the existing infrastructure of code and data pipelines, constantly exploring new technologies and eliminating bottlenecks.
You will experiment with various technologies in the domain of Machine Learning and big data processing.
You will work on a monitoring infrastructure for our data pipelines to ensure smooth and reliable data ingestion and calculation.
Requirements:
Passionate about data.
Holds a BSc degree in Computer Science\Engineering or a related technical field of study.
Has at least 4 years of software or data engineering development experience in one or more of the following programming languages: Python, Java, or Scala.
Has strong programming skills and knowledge of Data Structures, Design Patterns and Object Oriented Programming.
Has good understanding and experience of CI/CD practices and Git.
Excellent communication skills with the ability to provide constant dialog between and within data teams.
Can easily prioritize tasks and work independently and with others.
Conveys a strong sense of ownership over the products of the team.
Is comfortable working in a fast-paced dynamic environment.
Advantage:
Has experience with containerization technologies like Docker and Kubernetes.
Experience in designing and productization of complex big data pipelines.
Familiar with a cloud provider (AWS / Azure / GCP).
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
Required Big Data Engineer Team Lead
We are an innovative technology company led by data scientists and engineers devoted to mobile app growth. Our proprietary ad platform is powered by machine learning and is constantly improving its distribution algorithms.
We deliver valuable results and insights for a fast-growing clientele of major app developers using elite programmatic user acquisition and retargeting technologies.
Our state-of-the-art machine learning technology analyzes 50TB of raw data per day to produce millions of ad recommendations in real-time. This data is used to power our machine learning predictions, business-critical metrics, and analytics to power our decision-making.
As a Big Data Team Lead, you will lead a team focused on building scalable, algorithm-heavy data products rather than owning the underlying data infrastructure.
Your team will be responsible for implementing complex business and optimization logic-often incorporating multiple algorithms using Peta-Byte scale data processing (primarily PySpark). A core part of the role is ensuring these data products are explainable, observable, and trusted by Data Science, BI, Product, and business stakeholders.
You will work closely with the Data Infrastructure TL, Data Science, BI, and Product to turn advanced logic into production-grade, transparent, and measurable systems.
Responsibilities:
Lead development of scalable, algorithm-heavy data products using PySpark and Implement and maintain complex, multi-stage data flows with multiple interacting algorithms.
Translate business and algorithmic requirements into clear, testable data logic. Ensuring explainability of outputs through intermediate artifacts, metadata, and documentation & Defining and monitoring; observability signals for data quality, algorithm health, and business impact.
Mentor engineers on reasoning about complex logic, edge cases, and failure modes.
Requirements:
2+ years of experience in technical leadership or leading complex projects.
6+ years of experience as a Data / Backend Engineer in data-intensive systems.
Strong production experience with PySpark.
Excellent SQL skills for complex analysis, validation, and BI-facing data models.
Proven experience implementing complex algorithms and business logic at scale.
Strong understanding of data correctness, edge cases, and validation strategies.
Advantage:
Experience with algorithm explainability and data observability.
Background working closely with Data Science / ML teams.
Experience with large-scale Spark batch or streaming pipelines.
AWS-based data platforms experience.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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עדכון קורות החיים לפני שליחה
8515719
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
23/12/2025
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.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8470086
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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 :)
5 ימים
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
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8511741
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