דרושים » דאטה » Senior Data Engineer

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.

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.

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.

we are looking for a Senior Data Engineer I.
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.
21679

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.

we are looking for a Data Engineer.
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 ore.
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.
20718

We are looking for a Staff Data Platform Engineer to join our Engineering team and lead the evolution of our next-generation data platform. In this high-impact role, you will operate as a player-coach: you will be the technical visionary responsible for designing the ecosystem, while remaining deeply hands-on to implement scalable, secure, and intelligent solutions that power everything from operational reporting to advanced GenAI applications.
You will bridge the gap between complex business requirements and technical execution, advocating for a data-first culture. This role offers a clear growth path: while it currently starts as an individual contributor position, it has the potential to evolve into a leadership role.
About the Role:
Architecture & Hands-on Execution: Design and actively build a comprehensive data platform. You will not just oversee infrastructure; you will write the core code and build tools that support diverse workloads-from operational reporting to complex analytical queries.
Strategic & Technical Delivery: Partner with product managers to translate business objectives into technical strategies, then lead the engineering effort to deliver them.
Technology Evaluation: Continuously evaluate, prototype, and select best-in-class technologies to future-proof our data stack.
Technical Leadership & Mentorship: Act as a primary advocate for platform adoption. You will foster a community of practice around data engineering, mentoring senior and mid-level engineers to elevate the team's technical bar.
Governance & Quality: Implement and automate robust frameworks for Data Discovery, Quality, and Governance, ensuring solutions are trustworthy and compliant with financial regulations.

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

We are looking for an experienced and passionate Data Engineer to join the Data Engineering Team in our rapidly growing TLV R&D site!
You will be instrumental in maintaining current pipelines and expanding our data semantic layer to support both traditional analytics and our future AI/ML initiatives.
Responsibilities include working alongside developers from the BI and Backend teams, architects and business decision makers in order to implement data pipelines and improve data architecture and infrastructure.
The Data Engineering Team focuses on building long term, scalable self-service solutions for the organizational growing data needs.
What You'll Do:
Design & Build Robust Pipelines: Develop, deploy, and maintain scalable, highly reliable, and idempotent ELT data pipelines using Python and orchestration tools like Airflow.
Own the Data Model: Lead data transformation and modeling efforts within our cloud data warehouse (e.g., Snowflake, AWS) using dbt, ensuring adherence to modern analytics engineering best practices (modularity, DRY principles, and clear separation of staging and data marts).
Expand the Semantic Layer: Architect and grow our centralized semantic layer to establish a "single source of truth" for business metrics, powering both traditional BI dashboards and upcoming AI initiatives.
Champion Data Quality & Reliability: Implement rigorous data validation, testing, and monitoring to ensure data integrity and build trust with downstream consumers.
Enable Self-Service Analytics: Design intuitive, long-term data infrastructure solutions that empower business stakeholders, analysts, and developers to easily and independently query organizational data.
Cross-Functional Collaboration: Partner closely with Backend developers, BI analysts, architects, and business decision-makers to translate complex business requirements into efficient technical architectures.

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.