דרושים » דאטה » Data Engineer

Required Senior Data Engineer
What You'll Do:
Shape the Future of Data- Join our mission to build the foundational pipelines and tools that power measurement, insights, and decision-making across our product, analytics, and leadership teams.
Develop the Platform Infrastructure - Build the core infrastructure that powers our data ecosystem including the Kafka events-system, DDL management with Terraform, internal data APIs on top of Databricks, and custom admin tools (e.g. Django-based interfaces).
Build Real-time Analytical Applications - Develop internal web applications to provide real-time visibility into platform behavior, operational metrics, and business KPIs integrating data engineering with user-facing insights.
Solve Meaningful Problems with the Right Tools - Tackle complex data challenges using modern technologies such as Spark, Kafka, Databricks, AWS, Airflow, and Python. Think creatively to make the hard things simple.
Own It End-to-End - Design, build, and scale our high-quality data platform by developing reliable and efficient data pipelines. Take ownership from concept to production and long-term maintenance.
Collaborate Cross-Functionally - Partner closely with backend engineers, data analysts, and data scientists to drive initiatives from both a platform and business perspective. Help translate ideas into robust data solutions.
Optimize for Analytics and Action - Design and deliver datasets in the right shape, location, and format to maximize usability and impact - whether thats through lakehouse tables, real-time streams, or analytics-optimized storage.
You will report to the Data Engineering Team Lead and help shape a culture of technical excellence, ownership, and impact.

We're seeking an outstanding and passionate Data Platform Engineer to join our growing R&D team.
You will work in an energetic startup environment following Agile concepts and methodologies. Joining the company at this unique and exciting stage in our growth journey creates an exceptional opportunity to take part in shaping Finaloop's data infrastructure at the forefront of Fintech and AI.
What you'll do:
Design, build, and maintain scalable data pipelines and ETL processes for our financial data platform.
Develop and optimize data infrastructure to support real-time analytics and reporting.
Implement data governance, security, and privacy controls to ensure data quality and compliance.
Create and maintain documentation for data platforms and processes
Collaborate with data scientists and analysts to deliver actionable insights to our customers.
Troubleshoot and resolve data infrastructure issues efficiently
Monitor system performance and implement optimizations
Stay current with emerging technologies and implement innovative solutions
Tech stack: AWS Serverless, Python, Airflow, Airbyte, Temporal, PostgreSQL, Snowflake, Kubernetes, Terraform, Docker.

We are making the future of Mobility come to life starting today.
At our company we support the worlds largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization.
At the heart of our platform lies the data infrastructure, driving advanced machine learning models and optimization algorithms. As the owner of data pipelines, you'll tackle diverse challenges spanning optimization, prediction, modeling, inference, transportation, and mapping.
As a Senior Data Engineer, you will play a key role in owning and scaling the backend data infrastructure that powers our platformsupporting real-time optimization, advanced analytics, and machine learning applications.
What You'll Do
Design, implement, and maintain robust, scalable data pipelines for batch and real-time processing using Spark, and other modern tools.
Own the backend data infrastructure, including ingestion, transformation, validation, and orchestration of large-scale datasets.
Leverage Google Cloud Platform (GCP) services to architect and operate scalable, secure, and cost-effective data solutions across the pipeline lifecycle.
Develop and optimize ETL/ELT workflows across multiple environments to support internal applications, analytics, and machine learning workflows.
Build and maintain data marts and data models with a focus on performance, data quality, and long-term maintainability.
Collaborate with cross-functional teams including development teams, product managers, and external stakeholders to understand and translate data requirements into scalable solutions.
Help drive architectural decisions around distributed data processing, pipeline reliability, and scalability.

As a Big Data & GenAI Engineering Lead within our company's Data & AI Department, you will play a pivotal role in building the data and AI backbone that empowers product innovation and intelligent business decisions. You will lead the design and implementation of our companys next-generation lakehouse architecture, real-time data infrastructure, and GenAI-enriched solutions, helping drive automation, insights, and personalization at scale. In this role, you will architect and optimize our modern data platform while also integrating and operationalizing Generative AI models to support go-to-market use cases. This includes embedding LLMs and vector search into core data workflows, establishing secure and scalable RAG pipelines, and partnering cross-functionally to deliver impactful AI applications.
As a Big Data & GenAI Engineering Lead in our company you will...
Design, lead, and evolve our companys petabyte-scale Lakehouse and modern data platform to meet performance, scalability, privacy, and extensibility goals.
Architect and implement GenAI-powered data solutions, including retrieval-augmented generation (RAG), semantic search, and LLM orchestration frameworks tailored to business and developer use cases.
Partner with product, engineering, and business stakeholders to identify and develop AI-first use cases, such as intelligent assistants, code insights, anomaly detection, and generative reporting.
Integrate open-source and commercial LLMs securely into data products using frameworks such as LangChain, or similar, to augment AI capabilities into data products.
Collaborate closely with engineering teams to drive instrumentation, telemetry capture, and high-quality data pipelines that feed both analytics and GenAI applications.
Provide technical leadership and mentorship to a cross-functional team of data and ML engineers, ensuring adherence to best practices in data and AI engineering.
Lead tool evaluation, architectural PoCs, and decisions on foundational AI/ML tooling (e.g., vector databases, feature stores, orchestration platforms).
Foster platform adoption through enablement resources, shared assets, and developer-facing APIs and SDKs for accessing GenAI capabilities.

Were looking for an experienced and passionate Staff Data Engineer to join our Data Platform group in TLV as a Tech Lead. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of our companys data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives our company toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
In this role youll
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across our company to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization.

We are seeking talented and passionate Data Engineer to join our growing Data team. In this pivotal role, you will be instrumental in designing, building, and optimizing the critical data infrastructure that underpins innovative creative intelligence platform. You will tackle complex data challenges, ensuring our systems are robust, scalable, and capable of delivering high-quality data to power our advanced AI models, customer-facing analytics, and internal business intelligence. This is an opportunity to make a significant impact on our product, contribute to a data-driven culture, and help solve fascinating problems at the intersection of data, AI, and marketing technology.
Key Responsibilities
Architect & Develop Data Pipelines: Design, implement, and maintain sophisticated, end-to-end data pipelines for ingesting, processing, validating, and transforming large-scale, diverse datasets.
Manage Data Orchestration: Implement and manage robust workflow orchestration for complex, multi-step data processes, ensuring reliability and visibility.
Advanced Data Transformation & Modeling: Develop and optimize complex data transformations using advanced SQL and other data manipulation techniques. Contribute to the design and implementation of effective data models for analytical and operational use.
Ensure Data Quality & Platform Reliability: Establish and improve processes for data quality assurance, monitoring, alerting, and performance optimization across the data platform. Proactively identify and resolve data integrity and pipeline issues.
Cross-Functional Collaboration: Partner closely with AI engineers, product managers, developers, customer success and other stakeholders to understand data needs, integrate data solutions, and deliver features that provide exceptional value.
Drive Data Platform Excellence: Contribute to the evolution of our data architecture, champion best practices in data engineering (e.g., DataOps principles), and evaluate emerging technologies to enhance platform capabilities, stability, and cost-effectiveness.
Foster a Culture of Learning & Impact: Actively share knowledge, contribute to team growth, and maintain a strong focus on how data engineering efforts translate into tangible product and business outcomes.

a Senior Data Engineer to join its Research Engineering team. The Research Engineering teams mission is to enable research needs. We succeed when our research analysts, data scientists, and engineers have access to the data, tools, knowledge, and support to do their jobs painlessly and efficiently.

We build the foundational infrastructure and key applications that allow internal users to derive actionable insights from vast data. Both enablingand runningBig Data processing at the scale of hundreds of TB is a core part of what our team does, but were not just a Big Data team. We work across the tech stack in support of our mission to enable data-driven research and investigation, from back-end to front-end to data stores.

What you'll be doing:

Design, build, and maintain foundational infrastructure and key applications that allow people to effectively leverage proprietary and public data
Use modern technologies daily, such as: Snowflake, Databricks, Apache Spark, Elasticsearch, AWS, Kafka, and more
Expand and optimize data warehouse and lakehouseweighing tradeoffs between performance, cost, and user experienceacross continually larger and more complex datasets
Model data and define storage strategy, to ensure that data is intuitive for researchers to find, and easy and fast for them to access
Enhance analysts most-used web application, which gives them in-depth insight into every decision we make
Collaborate directly with colleagues from various disciplines: Analysts, Data Scientists, and other Engineers (all of whom write production code!)
Self-manage project planning, milestones, designs, and estimations
Hold yourself and others to a high standard when working with production systems. We take pride in our tests, monitoring & alerting abilities just as we do with our systems.
Debug complex problems across the whole stack

Were looking for a Data Engineer for the Insight Team to join our Data Group and a new team responsible for developing innovative features based on multiple layers of data. These features will power recommendation systems, insights, and more. This role involves close collaboration with the core teams within the Data Group, working on diverse data pipelines that tackle challenges related to scale and algorithmic optimization, all aimed at enhancing the data experience for our customers.
Where does this role fit in our vision?
Every role at our company is designed with a clear purposeto integrate collective efforts into our shared success, functioning as pieces of a collective brain. Data is everything, its at the heart of everything we do. The Data Group is responsible for shaping the experience of hundreds of thousands of users who rely on our data daily.
The Insight Team monitors user behavior across our products, leveraging millions of signals and time-series entities to power a personalized recommendation and ranking system. This enables users to access more unique and tailored data, optimizing their experience while maintaining a strong focus on the key KPIs that drive the success of our Data Group.
What will you be responsible for?
Develop and implement robust, scalable data pipelines and integration solutions within our Databricks-based environment.
Develop models and implement algorithms, with a strong emphasis on delivering high-quality results.
Leverage technologies like Spark, Kafka, and Airflow to tackle complex data challenges and enhance business operations.
Design innovative data solutions that support millions of data points, ensuring high performance and reliability.

Were looking for a Data Engineer to design and implement high-scale, data-intensive platforms, research and develop algorithmic solutions, and collaborate on key company initiatives. You will play a critical role within our core data teams, which are responsible for managing and optimizing our fundamental data assets.
Where does this role fit in our vision?
Every role at our company is designed with a clear purposeto integrate collective efforts into our shared success, functioning as pieces of a collective brain. Data is at the heart of everything we do. Our data engineers are responsible for building and maintaining the core products that power our business. The data teams own and manage the pipelines that generate our assets, with a strong focus on optimizing key company KPIs.
We leverage cutting-edge technologies to build and scale our data infrastructure. In this role, you will work closely with Data Scientists and Data Analysts on a daily basis, collaborating to develop innovative data solutions that drive business impact.
What will you be responsible for?
Solve Complex Business Problems with Scalable Data Solutions
Develop and implement robust, high-scale data pipelines to power our core assets.
Leverage cutting-edge technologies to tackle complex data challenges and enhance business operations.
Collaborate with Business Stakeholders to Drive Impact
Work closely with Product, Data Science, and Analytics teams to define priorities and develop solutions that directly enhance our core products and user experience.
Build and Maintain a Scalable Data Infrastructure
Design and implement scalable, high-performance data infrastructure to support machine learning, analytics, and real-time data processing.
Continuously monitor and optimize data pipelines to ensure reliability, accuracy, and efficiency.

As part of the Data Infrastructure group, youll help build our companys data platform for our growing stack of products, customers, and microservices.
We ingest our data from our operational DBs, telematics devices, and more, working with several data types (both structured and unstructured). Our challenge is to provide building tools and infrastructure to empower other teams leveraging data-mesh concepts.
In this role youll
Help build our companys data platform, designing and implementing data solutions for all application requirements in a distributed microservices environment
Build data-platform ingestion layers using streaming ETLs and Change Data Capture
Implement pipelines and scheduling infrastructures
Ensure compliance, data-quality monitoring, and data governance on our companys data platform
Implement large-scale batch and streaming pipelines with data processing frameworks
Collaborate with other Data Engineers, Developers, BI Engineers, ML Engineers, Data Scientists, Analysts and Product managers
Share knowledge with other team members and promote engineering standards.