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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

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:
What Were Looking For:
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.

Additional Skills:
Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Release Management, Security-First Mindset, User Experience (UX).
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across.
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build next-generation data stack.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll:
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals
Requirements:
7+ years as a BI Engineer or Data Engineer, with 2+ in a technical leadership or architect role
Proven experience managing complex data warehouses that serve multiple products and entire organizations
Strong expertise in data modeling, ELT development, and data warehouse methodologies
Advanced SQL skills and hands-on experience with Snowflake or similar cloud-native data warehouse platforms
Extensive experience with dbt for data transformation and modeling
Python and software development experience (a strong plus)
Excellent communication skills - you can mentor technical team members and explain complex data concepts to business stakeholders
Ready to work in an office environment most days of the 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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הגשת מועמדותהגש מועמדות
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Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for an experienced and passionate Data Group Tech Lead, Staff Engineer to join our Data Platform group in TLV. 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 data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives 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.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
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 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
דרישות:
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 NoS המשרה מיועדת לנשים ולגברים כאחד.
 
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הגשת מועמדותהגש מועמדות
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10/05/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
We are at a pivotal stage in building and scaling our data domain, and we are looking for a Data Engineer to join our growing BI team. This role goes beyond building pipelines. You will help shape our data platform as a shared product - supporting analytics, reporting, and decision-making across key company data domains such as Product, Sales, HR, and others. Your work will directly influence how stakeholders interact with data today and how the platform evolves in the years ahead.

What Youll Be Doing
Architect & Own: Lead the design and development of scalable data warehouse and BI solutions. You will make early-stage architectural decisions and own their long-term impact.
Infrastructure as a Product: Build core data infrastructure and developer experiences that others rely on, ensuring high availability and system reliability.
End-to-End ELT/ETL: Solve complex integration problems by sourcing data from structured and unstructured sources using Rivery, Python, and optimal ETL patterns.
Data Quality & Governance: Implement frameworks for schema evolution, anomaly detection, and data freshness. You will determine security models based on privacy requirements and evolve governance processes.
Strategic Collaboration: Partner with Engineers, Product Managers, and Data Analysts to conceptualize data needs and represent key insights in a meaningful way.
Optimization: Assist in owning production processes, optimizing complex code through advanced algorithmic concepts to manage operational cost-benefit tradeoffs.
Requirements:
Experience: 5+ years of experience in Data Engineering, Infrastructure, or Platform Engineering (ideally in organizations operating at a meaningful scale).
Technical Mastery: 5+ years of hands-on experience with Python and SQL. Deep proficiency in data modeling (Star/Snowflake schema) and DWH methodologies.
Cloud & Tools: Proven experience with Snowflake and AWS. Familiarity with Rivery or similar orchestration tools (like DBT) is a major advantage.
Production-First Mindset: Track record of leading data initiatives end-to-end from design and building to shipping and operating production flows.
Analytical Rigor: Ability to triage issues, resolve data quality problems, and design systems that handle system complexity with ease.
Education: Bachelors degree in Computer Science, Computer Engineering, or a relevant technical field.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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10/05/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Data Platform Engineer to join our community!
As a Senior Data Platform Engineer, you will play a key role in building and evolving Grips modern data platform - the infrastructure that powers product features and analytics across the company.

You will focus on designing and operating scalable, reliable data systems and platform tooling that support our Data Lakehouse, enabling engineers, analysts and research teams to work with data efficiently and with minimal friction.

Responsibilities
Design, build and operate a cloud-native modern data platform.
Develop and optimize data processing frameworks and pipelines across batch and streaming workloads.
Improve developer experience and platform usability through tooling and automation.
Lead and support large-scale data migrations and architectural improvements.
Drive best practices around infrastructure, CI/CD, testing, and system design.
Collaborate with developers, analysts, data scientists and other stakeholders to develop new products and features.
Contribute to a strong engineering culture of ownership, learning, and knowledge sharing.
Requirements:
5+ years of hands-on experience building scalable data infrastructure, particularly around data lake or data warehouse architectures.
Proven experience designing, building and operating production-grade systems and services.
Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and hands-on experience with modern data platforms and tools (e.g., Spark, Kafka, Airflow, dbt, open table formats, or similar).
Strong programming skills in Python and SQL.
Independent, proactive, and ownership-driven mindset.
Background in data platform engineering, backend engineering, DevOps, or DBA - strong advantage.
Experience with containerization technologies - advantage.
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 Senior Data Engineer to take ownership of our evolving data platform.
Our data environment is entering a significant growth phase. We are strengthening our Redshift-based warehouse, expanding our transformation capabilities with dbt, and investing in modern engineering standards across the stack.
In parallel, we are building a dedicated application layer for delivering data products. This role is responsible for designing and owning the data foundations that support it.
AI-assisted development is not a side experiment. It is a core part of how we engineer. We expect this role to actively leverage advanced AI development tools as part of daily work, accelerating design, implementation, validation and documentation while maintaining strong architectural judgment and production-level quality.
This position requires architectural thinking, long-term platform vision and the ability to lead complex initiatives from design through production in an AI-augmented engineering environment.
What You Will Do:
Own the architecture and evolution of our cloud-based Data Warehouse.
Lead complex data initiatives end to end, from requirements definition and technical design through implementation, deployment and post-production optimization.
Apply AI-assisted development workflows to improve engineering velocity, code quality and system reliability.
Design and evolve transformation standards and modeling practices using dbt as a strategic layer within the team.
Architect the data foundations that power our data-driven applications.
Translate business needs into structured, production-grade data solutions.
Drive technical standards, consistency and engineering discipline across the data stack.
Take full accountability for delivery, stability and long-term scalability of the systems you build.
Requirements:
8+ years of experience in Data Engineering with strong focus on modern cloud-based DWH architecture.
Proven experience leading projects end to end in production data environments.
Deep production experience with Redshift, dbt and orchestration frameworks such as Airflow.
Strong SQL expertise and solid understanding of dimensional modeling and transformation best practices.
Practical, daily experience using AI development tools as part of your engineering workflow.
Ability to critically evaluate AI-generated output and maintain high architectural and production standards.
Strong system design capabilities and full ownership mindset.
Experience supporting data products or application-facing data environments.
Ability to balance speed with quality and long-term architectural thinking.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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04/05/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're hiring a Data Engineer to join our growing team of analytics experts in order to help & lead the build-out of our data integration and pipeline processes, tools and platform.
The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
The right candidate must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our companys data architecture to support our next generation of products and data initiatives.
In this role, you will be responsible for:
Create ELT/Streaming processes and SQL queries to bring data to/from the data warehouse and other data sources.
Establish scalable, efficient, automated processes for large-scale data analyses.
Support the development of performance dashboards & data sets that will generate the right insight.
Work with business owners and partners to build data sets that answer their specific business questions.
Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making across the organization.
Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
Own the data lake pipelines, maintenance, improvements and schema.
Requirements:
BS or MS degree in Computer Science or a related technical field.
3-4 years of Python / Java development experience.
3-4 years of experience as a Data Engineer or in a similar role (BI developer).
3-4 years of direct experience with SQL (No-SQL is a plus), data modeling, data warehousing, and building ELT/ETL pipelines - MUST
Experience working with cloud environments (AWS preferred) and big data technologies (EMR,EC2, S3 ) - DBT is an advantage.
Experience working with Airflow - big advantage
Experience working with Kubernetes - advantage
Experience working with at least in one of the big data environments: Snowflake, Vertica, Hadoop (Impala/Hive), Redshift etc - MUST
Experience working with Spark - advantage
Exceptional troubleshooting and problem-solving abilities.
Excellent verbal/written communication & data presentation skills
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 Data Infra Tech Lead.
The Data Group builds and maintains the core data assets that power our products, from our Company and Contact databases to our Connect and Recommendation systems. The Data Tech Lead sits at the forefront of that mission, leading engineering innovation that directly shapes the experience of our growing user base and drives the evolution of intelligent data services.
This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.
Your impact and responsibilities:
Leading the design and development of scalable, high-performance data workflows, including both batch pipelines and real-time data products.
Defining, implementing, and enforcing engineering best practices related to code quality, testing, CI/CD pipelines, observability, and documentation.
Mentoring, supporting, and growing a team of data engineers, fostering a collaborative and high-performance engineering culture.
Identifying opportunities to create new data assets and features that expand product capabilities and value proposition.
Driving architectural decision-making in areas of data modeling, storage solutions, and compute resources within cloud environments such as Databricks and Snowflake.
Collaborating closely with cross-functional stakeholders- including Product, DevOps, and R&D - to ensure effective delivery and platform stability.
Promoting and championing a data-driven mindset across the organization, balancing technical rigor with business context and strategic goals.
Requirements:
Minimum 5 years of hands-on experience designing, building, and maintaining large-scale data pipelines for both batch processing and streaming use cases.
Deep expertise in Python and SQL, with a focus on writing clean, performant, and maintainable code.
Strong analytical and problem-solving skills, with the ability to break down complex technical challenges and align solutions to business objectives.
Solid background in data modeling, analytics, and designing architectures for scalability, performance, and cost efficiency.
Strong problem-solving skills and ability to work in a fast-paced, high-growth environment
Practical experience working with modern OLAP systems and cloud data platforms, including Databricks, Snowflake, or BigQuery.
Familiarity with AI agent protocols (such as A2A, MCP) and LLM-related technologies (e.g., vector databases, embeddings) is a plus.
AI-saviness, with comfort adopting AI tools and staying current with emerging AI trends and technologies.
Experience leading Task Forces and cross-domain projects
Bonus Points:
Experience with Elasticsearch, Databricks, and relational database management systems.
Strong understanding of cloud infrastructure (preferably Amazon Web Services), including networking, storage, identity and access management (IAM), and cost optimization.
Background in FinOps or cloud cost management frameworks - an advantage.
Management experience.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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עדכון קורות החיים לפני שליחה
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

We are looking for a talented Data Engineer to help build and enhance the data platform that supports analytics, operations, and data-driven decision-making across the organization. You will work hands-on to develop scalable data pipelines, improve data models, ensure data quality, and contribute to the continuous evolution of our modern data ecosystem.

Youll collaborate closely with Senior Engineers, Analysts, Data Scientists, and stakeholders across the business to deliver reliable, well-structured, and well-governed data solutions.


What Youll Do
Engineering & Delivery
Build, maintain, and optimize data pipelines for batch and streaming workloads.

Develop reliable data models and transformations to support analytics, reporting, and operational use cases.

Integrate new data sources, APIs, and event streams into the platform.

Implement data quality checks, testing, documentation, and monitoring.

Write clean, performant SQL and Python code.

Contribute to improving performance, scalability, and cost-efficiency across the data platform.

Collaboration & Teamwork

Work closely with senior engineers to implement architectural patterns and best practices.

Collaborate with analysts and data scientists to translate requirements into technical solutions.

Participate in code reviews, design discussions, and continuous improvement initiatives.

Help maintain clear documentation of data flows, models, and processes.

Platform & Process

Support the adoption and roll-out of new data tools, standards, and workflows.

Contribute to DataOps processes such as CI/CD, testing, and automation.

Assist in monitoring pipeline health and resolving data-related issues.
Requirements:
What Were Looking For:

2-5+ years of experience as a Data Engineer or similar role.

Hands-on experience with Snowflake (mandatory)-including SQL, modeling, and basic optimization.

Experience with dbt (or similar)-model development, tests, documentation, and version control workflows.

Strong SQL skills for data modeling and analysis.

Proficiency with Python for pipeline development and automation.

Experience working with orchestration tools (Airflow, Dagster, Prefect, or equivalent).

Understanding of ETL/ELT design patterns, data lifecycle, and data modeling best practices.

Familiarity with cloud environments (AWS, GCP, or Azure).

Knowledge of data quality, observability, or monitoring concepts.

Good communication skills and the ability to collaborate with cross-functional teams.


Nice to Have:

Exposure to streaming/event technologies (Kafka, Kinesis, Pub/Sub).

Experience with data governance or cataloging tools.

Basic understanding of ML workflows or MLOps concepts.

Experience with infrastructure-as-code tools (Terraform, CloudFormation).

Familiarity with testing frameworks or data validation tools.

Additional Skills:
Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Security-First Mindset, User Experience (UX)
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 strong, hands-on Data Engineer to join our team and play a key role in building our data infrastructure from the ground up. In this role, you will design and implement scalable data pipelines and platforms, supporting both batch and real-time use cases. You will work closely with analysts and stakeholders to deliver reliable, high-quality data solutions, and take full ownership of data flows - from ingestion to consumption. This is a great opportunity for an executor who enjoys building, moving fast, and making an impact.
What will your job look like?
Design, build, and maintain robust and scalable data pipelines (batch and real-time) end-to-end.
Design and implement scalable, flexible data architectures to support evolving business needs.
Build and manage data platforms, including data lakes and data warehouses.
Integrate multiple data sources (structured and unstructured) into a unified data platform using batch (ETL) and real-time streaming solutions.
Design and implement efficient data models, schemas, and database structures (SQL / NoSQL).
Develop and implement data quality processes to ensure accuracy, consistency, and reliability.
Monitor, optimize, and troubleshoot data infrastructure to meet performance and SLA requirements.
Requirements:
5+ years of hands-on experience as a Data Engineer, building data systems from scratch in dynamic environments.
Bachelors degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
Strong proficiency in Python and advanced SQL, with solid experience in data modeling.
Proven experience designing and building scalable data pipelines (batch and real-time), including streaming technologies such as Kafka.
Strong experience working with AWS, including services such as S3, Athena and DynamoDB.
Experience working with big data processing frameworks such as Spark, and columnar data formats (e.g., Parquet).
Hands-on experience with workflow orchestration tools such as Airflow.
Strong ownership and execution mindset, with excellent problem-solving skills and high attention to detail, and the ability to collaborate effectively and deliver in ambiguous, fast-paced environments.
Experience with data platform technologies such as Databricks, Snowflake - Advantage.
Experience building data platforms using modern lakehouse technologies (e.g., Iceberg) - Advantage.
Fluent in English.
This position is open to all candidates.
 
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עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
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