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לפני 22 שעות
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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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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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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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: 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.
 
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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 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
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תודה על שיתוף הפעולה
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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הגשת מועמדותהגש מועמדות
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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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הגשת מועמדותהגש מועמדות
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25/01/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a talented Data Engineer to join our Data team and spread our power. The Data team develops and maintains the infrastructure for internal data and product analytics. We are looking for data enthusiasts, independent, logical thinkers with a can-do approach and a passion for problem-solving. We run a SaaS-based stack using BigQuery, Snowflake and dbt.
WHAT YOU'LL DO
Design, build, and maintain data pipelines, datasets and catalogs for fast-growing products and business groups.
Develop self-service data analytics solutions and infrastructure.
Support ad hoc needs and requests of internal stakeholders.
Collaborate with analysts, engineers, and internal customers from Product, Finance, Revenue, and Marketing.
Requirements:
Bachelors or Masters degree in a relevant technical field, or equivalent hands-on experience in software development or DevOps.
3+ years of experience working as a Data Engineer, including end-to-end designing, orchestrating, and building cloud-based data pipelines (e.g., Airflow, Prefect, Dagster).
3+ years of experience with dimensional data modeling and data warehouse implementation, specifically MPP databases like BigQuery, Snowflake, and Redshift.
Strong knowledge of Python and Python-based data analysis tools such as Jupyter Notebooks and pandas.
Strong SQL writing skills. Ability to write highly performant queries.
Strong track record of executing projects independently in dynamic environments.
Fast understanding of data and business needs and ability to translate them into data models.
Team player with excellent communication skills.
Containerization (Docker): Essential for reproducible environments.
Knowledge of software engineering best practices: CI/CD concepts, code reviews, and unit testing.
ADVANTAGE
Production-level experience with dbt, including project design, transformation, testing, and documentation.
Infrastructure-as-Code (Terraform): Managing cloud resources (S3 buckets, IAM roles) via code.
CI/CD pipelines (GitHub Actions/Jenkins): Automating the testing and deployment of data models.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
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8515929
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
2 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an experienced Data Engineering Team Leader.

In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data and analytics platforms.

A day in the life and how youll make an impact:

Drive the technical strategy and roadmap for the data engineering function, ensuring alignment with overall business objectives.
Own the design, development, and evolution of scalable, high-performance data pipelines to enable diverse and growing business needs.
Establish and enforce a strong data governance framework, including comprehensive data quality standards, monitoring, and security protocols, taking full accountability for data integrity and reliability.
Lead the continuous enhancement and optimization of the data analytics platform and infrastructure, focusing on performance, scalability, and cost efficiency.
Champion the complete data lifecycle, from robust infrastructure and data ingestion to detailed analysis and automated reporting, to maximize the strategic value of data and drive business growth.
Requirements:
5+ years of Data Engineering experience (preferably in a startup), with a focus on designing and implementing scalable, analytics-ready data models and cloud data warehouses (e.g., BigQuery, Snowflake).
Minimum 3 years in a leadership role, with a proven history of guiding teams to success.
Expertise in modern data orchestration and transformation frameworks (e.g., Airflow, DBT).
Deep knowledge of databases (schema design, query optimization) and familiarity with NoSQL use cases.
Solid understanding of cloud data services (e.g., AWS, GCP) and streaming platforms (e.g., Kafka, Pub/Sub).
Fluent in Python and SQL, with a backend development focus (services, APIs, CI/CD).
Excellent communication skills, capable of simplifying complex technical concepts.
Experience with, or strong interest in, leveraging AI and automation for efficiency gains.
Passionate about technology, proactively identifying and implementing tools to enhance development velocity and maintain high standards.
Adaptable and resilient in dynamic, fast-paced environments, consistently delivering results with a strong can-do attitude.
B.Sc. in Computer Science / Engineering or equivalent.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8527969
סגור
שירות זה פתוח ללקוחות VIP בלבד
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 :)
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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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8504288
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