דרושים » דאטה » Data Platform Engineer

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 data ecosystem.

The groups mission is to build a state-of-the-art Data Platform that drives us 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 us 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 looking for a talented Senior Data Engineer to join us.
As a Data Engineer, you will be a key member of the data team, at the core of a data-driven company, developing scalable, robust data platforms and data models and providing business intelligence. You will work in an evolving, challenging environment with a variety of data sources, technologies, and stakeholders to deliver the best solutions to support the business and provide operational excellence.
If you are passionate about data, a team player, and proactive, we want to hear from you.
Responsibilities:
Design, Develop & Deploy Data Pipelines and Data Models on various Data Lake / DWH layers
Ingest data from and export data to multiple third-party systems and platforms (e.g., Salesforce, Braze, SurveyMonkey).
Architect and implement data-related microservices and products
Ensure the implementation of best practices in data management, including data lineage, observability, and data contracts.
Maintain, support, and refactor legacy models and layers within the DWH.

Required Senior Data Engineer (Analytics)
Tel Aviv
As a Senior Data Engineer, you will play a key role in shaping and driving our analytics data pipelines and solutions to empower business insights and decisions. Collaborating with a variety of stakeholders, you will design, develop, and optimize scalable, high-performance data analytics infrastructures using modern tools and technologies. Your work will ensure data is accurate, timely, and actionable for critical decision-making.
Key Responsibilities:
Lead the design, development, and maintenance of robust data pipelines and ETL processes, handling diverse structured and unstructured data sources.
Collaborate with data analysts, data scientists, product engineers and product managers to deliver impactful data solutions.
Architect and maintain the infrastructure for ingesting, processing, and managing data in the analytics data warehouse.
Develop and optimize analytics-oriented data models to support business decision-making.
Champion data quality, consistency, and governance across the analytics layer.
What your day might look like:
Leading the design and implementation of scalable data pipelines to support analytical workloads.
Collaborating with stakeholders to gather requirements, propose solutions, and align on data strategies.
Writing and optimizing ETL processes to ensure seamless integration of new data sources.
Designing analytics-focused data modeling solutions tailored for strategic decision-making.
Troubleshooting data issues and implementing measures to improve system reliability and accuracy.
Sharing knowledge and mentoring team members to promote a culture of learning and excellence.
This is an opportunity to make a significant impact by enabling data-driven decision-making at scale while growing your career in a dynamic, collaborative environment.

A growing tech company in the automotive space with hubs across the US and Israel. Our mission is to constantly disrupt the industry by creating groundbreaking technologies to help dealers build stronger, more resilient businesses. Our work happens in the fast lane as we bring AI-powered, data-driven solutions to a quickly evolving industry.

Our team consists of curious and creative individuals who are always looking to achieve the impossible. We are bold, collaborative, and goal-driven, and at our core, we believe every voice has value and can impact our bottom line.
If you are a creative, solutions-oriented individual who is ready to put your career in drive,the place for you!

We are looking for an experienced Data Engineering Tech Lead to join our team and make a real impact! In this hands-on role, you will drive the architecture, development, and optimization of our Data infrastructure, ensuring scalable and high-performance data solutions that support analytics, AI, and business intelligence needs. You will collaborate closely with analysts, Product, DevOps, and software engineers to cultivate a robust data ecosystem.

This position will report to the CISO and can be based out of Jerusalem or Tel-Aviv.

What you will be responsible for
Lead the design and implementation and maintenance of our DWH & Data Lake architecture to support both analytical and operational use cases.
Develop scalable ETL/ELT pipelines for ingestion, transformation, and optimization of structured and unstructured data.
Ensure data quality, governance, and security throughout the entire data lifecycle.
Optimize performance and cost-efficiency of data storage, processing, and retrieval.
Work closely with BI and analytics teams to guarantee seamless data integration with visualization tools.
Collaborate with stakeholders (BI teams, Product, and Engineering) to align data infrastructure with business needs.
Mentor and guide analysts, fostering a culture of best practices and professionalism.
Stay updated with industry trends and evaluate new technologies for continuous improvement.

We're looking for an experienced Data Engineer to work on our massive data processing pipeline and our new NextGen BI system to help us deliver more insights and scale from our current billion events a day to tens of billions of events.
Responsibilities:
Pull data from various data sources and integrate into the ETL process
Integrate Machine Learning models in ETL to deliver insights to Marketing, Product and CRM departments
Optimize workloads to reduce cost and improve performance
Work closely with analysts from Product, Marketing and Data Scientists to deliver insights from over a Billion daily events and over 50 Marketing channels.

We are seeking an experienced and innovative Data Engineer to join our dynamic team!
As a leading FinTech startup based in Tel Aviv, we are dedicated to providing comprehensive financial & all around solutions for small businesses. The ideal candidate will possess a strong background in data engineering, data warehousing, and data modeling. This role demands a talented professional who can design, develop, and maintain our data infrastructure, empowering stakeholders across the company to make data-driven decisions. If you are a talented, humble, and ambitious individual ready to make a significant impact in a rapidly scaling company, we invite you to join us on our journey to revolutionize services for small businesses worldwide.
About the Opportunity:
As a Data Engineer, you will play a pivotal role in establishing and enhancing our data infrastructure, empowering stakeholders across the company to make informed, data-driven decisions.
What youll be doing:
Engage with potential customers via phone, email, and online communication tools to follow up on inquiries and leads.
Build and maintain relationships with prospects, understanding their needs and offering tailored solutions.
Develop and deliver sales pitches that highlight the benefits of our services.
Guide customers through the sales process, from the initial conversation to closing the deal.
Assist in onboarding new customers, ensuring they have a smooth and positive experience with our platform.
Maintain accurate records of interactions, sales progress, and follow-up tasks using our CRM system.
Continuously refine your product knowledge to better assist prospects and customers.
Responsibilities:
Design, develop, and maintain scalable and efficient data warehouse that align with our goals and requirements
Utilize advanced data modeling techniques to create robust data structures supporting data services and analytics needs
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into the data warehouse
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency
Implement best practices for data warehouse and database performance tuning
Conduct thorough testing of data applications and implement robust validation processes
Collaborate closely with cross-functional teams including Developers, Data Scientists, Product Managers, and Squad Leaders to build the best possible high-quality data systems and services
Help scale the data infrastructure through the introduction of proper processes and practices.

We're seeking talented data engineers to join our rapidly growing team, which includes senior software and data engineers. Together, we drive our data platform from acquisition and processing to enrichment, delivering valuable business insights. Join us in designing and maintaining robust data pipelines, making an impact in our collaborative and innovative workplace.

Responsibilities
Design, implement, and optimize scalable data pipelines for efficient data processing and analysis.
Build and maintain robust data acquisition systems to gather, process, and store data from various sources.
Work closely with DevOps engineers, Data Science and Product teams to understand their requirements and provide data solutions that meet business objectives.
Proactively monitor data pipelines and production environments to identify and resolve issues promptly.
Implement best practices for data security, integrity, and performance.
Mentor and guide junior team members, sharing expertise and fostering their professional development

In this role, you will design and develop scalable data solutions, optimize data workflows, and support critical business processes. You will work with a variety of databases and big data tools in a cloud environment, focusing on data modeling, governance, and analytics.

What youll be doing:

Design, develop, and maintain end-to-end ETL pipelines, from gathering business requirements to implementation.
Work with multiple database technologies, especially BigQuery.
Optimize data models (DWH, fact & dimension tables, RI, SCDs) for performance and scalability.
Implement data governance best practices and maintain comprehensive documentation.
Utilize Big Data tools in cloud environments (GCP preferred).
Develop and support complex business workflows and data processes.
Design and implement monitoring systems to ensure data quality throughout the pipeline.
Workflow orchestration using Apache Airflow.
Collaborate with analysts and stakeholders to ensure high-quality data for business insights.
Support and optimize Tableau infrastructure for data visualization.

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.

venture-backed, fast-growing startup with a mission to use the power of Artificial Intelligence (AI) to get everyone access to higher quality healthcare at more affordable costs. Were looking for mission driven individuals to join our team and help us eliminate healthcare inequalities to build a better and healthier future.

Featured most recently in Forbes and Business Insider as a leading AI startup,a telehealth company that harnesses the power of technology to help provide the smartest digital healthcare platform to patients, hospital systems, and providers across the United States. Our AI powered application helps bring together the knowledge of thousands of doctors and anonymous medical data to provide the highest quality care to our patients. We offer a free symptom checker, 24/7 access to board-certified doctors, ability to refill prescriptions from your phone, and more. All within one application - no insurance or preauthorization required.
was founded in 2016, and has partnered with visionary and leading hospital systems and providers such as Cedars-Sinai, Mayo Clinic, and Elevance Health. Join us on our mission to help provide better healthcare for less.

About the Role
Our data engineering team is looking for an experienced professional with expertise in SQL, Python, and strong data modeling skills. In this role, you will be at the heart of our data ecosystem, designing and maintaining high-quality data pipelines and models that drive decision-making across the organization.

You will play a key role in ensuring data quality, building scalable systems, and supporting cross-functional teams with clean, accurate, and actionable data.

What you will do:
Design, develop, and optimize scalable data pipelines, ensuring data is clean, accurate, and ready for analysis.
Build and maintain robust data models that support clinical, business intelligence and operational needs.
Work closely with data analysts, data scientists, engineers and cross-functional teams to understand data requirements and deliver high-quality solutions.
Implement and enforce data quality standards, monitoring, and best practices across systems and pipelines.
Collaborate on the design and implementation of database schemas to support analytical and transactional workloads.
Manage and optimize large-scale data storage and processing systems to ensure reliability and performance.