דרושים » דאטה » Data 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 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.

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.

We are seeking a Senior Data Engineer to join our dynamic data team. In this role, you will design, build, and maintain robust data systems and infrastructure that support data collection, processing, and analysis. Your expertise will be crucial in developing scalable data pipelines, ensuring data quality, and collaborating with cross-functional teams to deliver actionable insights.

Key Responsibilities:

Design, develop, and maintain scalable ETL processes for data transformation and integration.
Build and manage data pipelines to support analytics and operational needs.
Ensure data accuracy, integrity, and consistency across various sources and systems.
Collaborate with data scientists and analysts to support AI model deployment and data-driven decision-making.
Optimize data storage solutions, including data lakehouses and databases, to enhance performance and scalability..
Monitor and troubleshoot data workflows to maintain system reliability.
Stay updated with emerging technologies and best practices in data engineering.

We are looking for a Data Engineer to join our team and play a key role in designing, building, and maintaining scalable, cloud-based data pipelines. You will work with AWS (Redshift, S3, Glue, Managed Airflow, Lambda) to integrate, process, and analyze large datasets, ensuring data reliability and efficiency.

Your work will directly impact business intelligence, analytics, and data-driven decision-making across the

What Youll Do:
ETL & Data Processing: Develop and maintain ETL processes, integrating data from various sources (APIs, databases, external platforms) using Python, SQL, and cloud technologies.
Cloud & Big Data Technologies: Implement solutions using PySpark, Databricks, Airflow, and cloud platforms (AWS) to process large-scale datasets efficiently.
Data Modeling: Design and maintain logical and physical data models to support business needs.
Optimization & Scalability: Improve process efficiency and optimize runtime performance to handle large-scale data workloads.
Collaboration: Work closely with BI analysts and business stakeholders to define data requirements and functional specifications.
Monitoring & Troubleshooting: Ensure data integrity and reliability by proactively monitoring pipelines and resolving issues.
Data Modeling: Design and maintain logical and physical data models to support analytics and operational needs

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.

Were looking for a Senior Data Engineer to help scale our data platform and deliver reliable, high-quality data services to both internal teams and external customers. If you thrive on solving complex data challenges, collaborating with diverse stakeholders, and building scalable systems that last, wed love to meet you.

What Youll Own:

Design and implement scalable ETL pipelines using Apache Spark and related technologies.
Build robust data services to support multiple internal teams, including product and analytics.
Architect end-to-end data solutions and translate them into actionable engineering plans.
Maintain clean, reliable data interfaces for microservices and systems requiring accurate, timely data.
Collaborate closely with product teams to understand data needs and co-create solutions.
Ensure observability, data quality, and pipeline reliability through monitoring and automated validation.
Participate in code reviews, architecture discussions, and mentor less experienced engineers.

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.

Required Data Engineer, Product Analytics
As a Data Engineer, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs, Threads). Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide.
In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across to optimize growth, strategy, and user experience for our 3 billion plus users, as well as our internal employee community.
You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining us, you will become part of a world-class data engineering community dedicated to skill development and career growth in data engineering and beyond.
Data Engineering: You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, design logging solutions, and create scalable data models. Ensuring data security and quality, and with a focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems.
Product leadership: You will use data to shape product development, identify new opportunities, and tackle upcoming challenges. You'll ensure our products add value for users and businesses, by prioritizing projects, and driving innovative solutions to respond to challenges or opportunities.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Engineer, Product Analytics Responsibilities
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Define and manage Service Level Agreements for all data sets in allocated areas of ownership
Solve challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
Improve logging
Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
Influence product and cross-functional teams to identify data opportunities to drive impact.

We are looking for a Data Engineering Team Lead to drive the development and optimization of our data infrastructure.

So, what will you be doing all day?

Lead & Mentor: Provide technical leadership and mentorship, setting clear goals, fostering innovation, managing stakeholders and guiding the professional growth of the team.
Data Infrastructure Development: Design and enhance scalable data architectures and pipelines to support current and future business needs.
ETL & Data Processing: Develop and maintain ETL processes, integrating data from various sources (APIs, databases, external platforms) using Python, SQL, and cloud technologies.
Cloud & Big Data Technologies: Implement solutions using PySpark, Databricks, Airflow, and cloud platforms (AWS) to process large-scale datasets efficiently.
Monitoring & Optimization: Ensure system reliability, observability, and performance using monitoring, logging, and alerting tools.
Collaboration & Stakeholder Engagement: Work closely with BI analysts, business stakeholders, and cross-functional teams to define data requirements and enable self-service BI capabilities.
Data Modeling: Design and maintain logical and physical data models to support analytics and operational needs.