לוח משרות דרושים הייטק דאטה בתל אביב יפו

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. 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
Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
Define and manage Service Level Agreements for all data sets in allocated areas of ownership
Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
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.

Required Data Science Manager
As a Data Science Manager, you will help shape the future of the experiences we build for billions of people and hundreds of millions of businesses, creators, and partners around the world. You will apply your people leadership, project management, analytical, and technical skills, creativity, and product intuition to one of the largest data sets in the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will influence product strategy and investment decisions with data, be focused on impact, and lead and grow a impact oriented team. By joining us, you will become part of the analytics community dedicated to skill development and career growth in analytics and beyond. About the role: Product leadership: You will use data to understand the product and business ecosystem, quantify new opportunities, identify upcoming challenges, and shape product development to bring value to people, businesses, and us. You will help develop strategy and support leadership in prioritizing what to build and setting goals for execution. Analytics: You will guide product teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them. Communication and influence: You wont simply present data, but tell data-driven stories. You will convince and influence leaders using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner. People leadership: You will inspire, lead and grow a team of data scientists and data science leaders.
Data Science Manager Responsibilities
Lead a team of data scientists to develop strategies for our products that serve billions of people and hundreds of millions of businesses, creators, and partners around the world
Drive analytics projects end-to-end in partnership with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
Influence product direction through clear and compelling presentations to leadership
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
Contribute towards advancing the Data Science discipline, including but not limited to driving data best practices (e.g. analysis, goaling, experimentation), improving analytical processes, scaling knowledge and tools, and mentoring other data scientists.

We are seeking a results-driven Analytics Team Lead with a minimum of 4 years in leadership roles, preferably within Fintech or B2C. You will lead a team of 5+ multi-domain analysts, focusing purely on high-level analysis and business logic. This role does not involve ETL, data modeling, or pipeline management; it is dedicated to extracting value and driving strategy.
Key Responsibilities:
Team Management: Lead the sprint and backlog for a diverse team of 5+ analysts.
Methodology: Develop and implement standardized analytical frameworks and A/B testing rigor.
Operational Efficiency: Audit and optimize internal workflows to eliminate double-work and manual inefficiencies.
Metric Ownership: Define departmental North Star metrics and proactively educate stakeholders on change drivers.
Execution: Maintain a hands-on approach to meet deadlines and push cross-functional projects to completion.
AI Integration: Build and deploy AI tools/frameworks to assist the team in faster insight generation.

Were looking for a Data Engineer to join our Data Labs (DL) department, which specializes in professional services for our super-premium customers. This role will report to our DL (Datalabs) Data Science Team Manager in the R&D.
Why is this role so important at our company?
we are a data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As part of this role, you will create and support a complex data model pipeline that helps analyze the petabytes of data we receive from various sources, and research and develop new features and capabilities for our product solutions
As a data engineer in the Datalabs team, you will work on the very core of the company. Part of your role will be to create processes that help turn raw data into usable metrics and leverage AI models and statistical algorithms to support out-of-the-box requests from customers who want custom data labs. The Datalabs departments business-oriented nature also means you will be supporting a team of analysts and data scientists who interact directly with customers. Together with them, you will translate the voice of these customers into best-in-class data labs.
So, what will you be doing all day?
Building and maintaining our big-data pipelines
Take a major part in designing and implementing complex high-scale systems using a large variety of technologies
Be part of a team with smart and motivated engineers, and data scientists, to collaborate on the planning, development, and maintenance of our products
Implement solutions in the AWS cloud environment, and work in Databricks with PySpark.

We are looking for a Data Operations Team Lead to lead and scale our data operations function. This role sits at the intersection of data, algorithms, and operations, and is critical to the success of our computer vision and AI models.
You will lead a distributed team responsible for data collection, annotation, quality control, and delivery, while working closely with Algorithm teams to understand model needs, prioritize requests, and ensure reliable, high-quality data pipelines.
This is a hands-on leadership role - you will manage people and processes, but also actively design, build, and improve data workflows.
Responsabilities
Lead and manage the Data Operations team, including annotation teams in Israel and a large remote team in India
Serve as the primary interface between Data Operations and Algorithm teams: understand model requirements, prioritize tasks, and plan data delivery
Own end-to-end data workflows, from model improvement needs through data definition, annotation guidelines, execution, and delivery
Ensure high data quality through close monitoring, validation, troubleshooting, and root-cause analysis
Design and maintain clear annotation guidelines, documentation, and training materials
Closely manage remote annotation teams, including weekly syncs, hands-on oversight, and deadline management
Own and operate the annotation pipeline using industry tools (e.g., CVAT)
Monitor progress, track performance, and continuously improve efficiency and quality
Own annotation budgets, monthly reporting, and validation of hours and outputs
Evaluate, benchmark, and implement new tools and processes in the data and annotation domain
Work hands-on with scripts, AI tools, and monitoring systems as needed to support data quality and operations.

As a Data Scientist , you will be a part of a large and innovative data science group, working closely with Dev teams and product managers, to create business value through Data Science and Machine Learning methods using cutting edge technology, on large and diverse datasets.

The Role consists of understanding customers' needs and product requirements, exploring data, identifying and defining functionality from conception to delivery, creating and improving algorithms and ML pipelines, building measurement tools, providing data visualizations, and more.

Deliver end-to-end ML products - including data processing, problem analysis, research, model development, validation and metrics, implemented in production and with online testing.

We are seeking a talented and motivated Senior Data Scientist to join our AI team. In this role, you will lead the development of our best-in-class conversational heart health agent. You will work on highly complicated challenges, spanning from deep research to full-scale production. Your work will leverage cutting-edge Generative AI and agentic architectures to help solving one of the world's most significant and urging clinical issues: cardiovascular disease. Your contribution will directly impact healthcare practices and enhance the well-being of individuals globally.
Responsibilities
You will take ownership of designing and building a conversational heart health agent, utilizing advanced LLM techniques, RAG (Retrieval-Augmented Generation), and flow engineering.
You will architect and implement complex agentic and multi-agentic graphs using tools like LangChain and LangGraph to handle intricate clinical logic and user interactions.
You will not just research; you will write production-grade code. You will be responsible for optimizing, deploying, and maintaining these systems in a live environment.
You will implement robust monitoring and debugging workflows for agentic products (using tools like LangFuse or LangSmith) to ensure safety, accuracy, and performance.
You will work closely with product managers and clinical experts to translate clinical research into digital insights and conversational flows that will be used on a daily basis.
You will innovate and make new ideas happen fast, in an agile way, keeping up with the rapidly evolving landscape of GenAI.

Required Senior Data Engineer
About the Role
Our Senior Data Engineer will play an essential role by building the underlying infrastructures, collecting, storing, processing and analyzing large sets of data, while collaborating with researchers, architects, and engineers, in order to design and build high-quality data processing for our flows.
In this role, you are responsible for end-to-end development of the data pipeline and data models, working with major data flow that includes structured and unstructured data. You will also hold responsibility for operating parts of our production system. Your focus will be on developing and integrating systems that retrieve and analyzing data that influence people's lives. This role for our Tel Aviv office is a hybrid role working at least two days per week in the office.
Our Technologies stack: Python, Spark, Airflow, DBT, Kafka, AWS, Snowflake, Docker, Kubernetes, MongoDB, Redis, Postgres, Elasticsearch, and more.
The ideal candidate will be
A technology enthusiast - who loves data and get shiver excitement from tech innovations.
Desire to know how things work and a greater desire to improve them.
Intellectual curiosity to find unusual ways to solve problems.
Comfortable taking on challenges and learning new technologies.
Comfortable working in a fast-paced dynamic environment.

We are building the next generation of digital heart-health products and our data platform is the foundation.
Were looking for a Data Platform Team Lead to own and evolve an AI-first, cloud-native data platform that already:
Serves 100+ data users across the company
Powers ML models impacting thousands of users every day
Supports production systems in a company that literally saves lives
You will lead a growing team of 4 data engineers and 1 BI developer, and work in close, day-to-day partnership with Product, Analytics, Data Science & Engineering
Our future is serving millions of users across multiple products in the heart-health ecosystem. This role owns the platform that will scale us there. We are intentionally building an AI-first / agentic data platform.
That means:
Automating table creation, validation, and testing
Agent-driven monitoring for data quality, freshness, and failures
Using agents to generate and maintain documentation
Reducing manual operational overhead so humans focus on architecture, leverage, and product impact
You will have full organizational support to rethink how a modern data platform should work in an AI-native environment, not incremental improvements, but fundamental design decisions.
Our Technologies stack: Python, Spark, Airflow, DBT, Kafka, AWS (Glue, EMR, S3, Athena and more), Snowflake, Docker, Kubernetes, MongoDB, Redis, Postgres, Elasticsearch, and evolving
Responsibilities:
Platform Leadership & Team Management: Lead, mentor, and grow a team of senior data engineers and BI developers. Set a high bar for technical quality, ownership, and delivery.
Core Data Platform Architecture: Own the design, evolution, and reliability of our cloud-native data platform, balancing scalability, cost, security, and developer velocity.
Deep Collaboration with R&D: Work closely with product, engineering, and ML teams to ensure the data platform enables fast experimentation, production ML, and new product development.
Production-Grade Data Systems: Oversee end-to-end data pipelines, streaming and batch processing, semantic layers, and analytics foundations that serve the entire organization.
Operational Excellence: Ensure data quality, freshness, observability, and incident response meet the standards of a mission-critical system.

We act as the central nervous system for engineering, enabling platform teams to unify their stack and expose it as a governed layer through golden paths for developers and AI agents.
By combining rich engineering context, workflows, and actions, we help organizations transition from manual processes to autonomous, AI-assisted engineering workflows while maintaining control and accountability.
As a product-led company, we believe in building world-class platforms that fundamentally shape how modern engineering organizations operate.
What youll do:
Lead the design and development of scalable and efficient data lake solutions that account for high-volume data coming from a large number of sources both pre-determined and custom.
Utilize advanced data modeling techniques to create robust data structures supporting reporting and analytics needs.
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into a data lake that will serve our company's users.
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency.
Collaborate with cross-functional teams (product, analytics, and R&D) to enhance our company's data solutions.
Who youll work with:
Youll be joining a collaborative and dynamic team of talented and experienced developers where creativity and innovation thrive.
You'll closely collaborate with our dedicated Product Managers and Designers, working hand in hand to bring our developer portal product to life.
Additionally, you will have the opportunity to work closely with our customers and engage with our product community. Your insights and interactions with them will play an important role to ensure we deliver the best product possible.
Together, we'll continue to empower platform engineers and developers worldwide, providing them with the tools they need to create seamless and robust developer portals. Join us in our mission to revolutionize the developer experience!

We are seeking a Senior Data Engineer to join our Data team,
The Data team develops and maintains the infrastructure for internal data and product analytics,
In this role, you will design and manage complex data pipelines and work closely with data analysts,
software engineers, and other stakeholders to continuously improve data processes and solutions.
What you will do:
Architect, develop, and maintain scalable, end-to-end data pipelines from diverse data sources
Monitor and maintain data systems, ensuring uptime, reliability, and stability
Provide technical expertise and insights to shape overall data strategy and best practices
Strong team player with excellent communication skills.

Were looking for an Analytics Engineer to join our team and play a key role in shaping how data drives our product and business decisions.
This role is perfect for someone who enjoys working at the intersection of data, product, and strategy. While Product Analysts focus on turning data into insights, youll focus on building the strong data foundations that make those insights possible. You wont just run queries; you will design the data architecture and own the "source of truth" tables that power our strategic decision-making.
Youll work closely with our Growth and Solutions teams, helping them move faster and smarter by making sure the data behind Generative AI, Data-as-a-Service (DaaS), and advanced product models is clear, reliable, and easy to use. Your work will have a direct impact on how we build, scale, and innovate our products.
What Youll Do:
Define the Source of Truth: Take raw, complex data and transform it into clean, well-structured tables that Product Analysts and Business Leads can use for high-stakes decision-making.
Translate Strategy into Logic: Work with Product, Growth, and Solutions leads to turn abstract concepts (like "Activation," "Retention," or "Feature Adoption") into precise SQL definitions and automated datasets.
Enable High-Tech Initiatives: Partner with our AI and DaaS specialists to ensure they have the structured data foundations they need to build models and external data products.
Optimize for Usability: Ensure our data is not just "there," but easy to use. You will design the data logic that powers our most important product dashboards and growth funnels.
Maintain Data Integrity: Act as the guardian of our metrics. You will ensure that the numbers used across our product and business reports are consistent, reliable, and logical.

Were looking for a Data Engineer to join our team and help shape a modern, scalable data platform. Youll work with cutting-edge AWS technologies, Spark, and Iceberg to build pipelines that keep our data reliable, discoverable, and ready for analytics.

Whats the Job?
Design and maintain scalable data pipelines on AWS (EMR, S3, Glue, Iceberg).
Transform raw, semi-structured data into analytics-ready datasets using Spark.
Automate schema management, validation, and quality checks.
Optimize performance and costs with smart partitioning, tuning, and monitoring.
Research and evaluate new technologies, proposing solutions that improve scalability and efficiency.
Plan and execute complex data projects with foresight and attention to long-term maintainability.
Collaborate with engineers, analysts, and stakeholders to deliver trusted data for reporting and dashboards.
Contribute to CI/CD practices, testing, and automation.

Were looking for a Senior Data Engineer in the Data Collection Ingest team to contribute to the design and coding of data ingestion services & pipelines. This role involves working as part of a team that handles millions of requests per minute across multiple servers, and is responsible for a wide-range of data pipelines, processing billions of events each day.
Why is this role so important?
As the most trusted platform for measuring online behavior, millions of people rely on insights daily as the ground truth for their knowledge of the digital world. Producing these insights requires large scale raw data to be ingested reliably in high scale to provide stable signals for analysis. As a Data Engineer you will have the opportunity to perform hands-on work and own raw data ingestion pipeline end-to-end. Your work will have a direct impact on the quality and reliability of our data and the insights that our products are delivering to our customers.

Were looking for a Big Data Engineer to develop and integrate systems that retrieve, process and analyze data from around the digital world, generating customer-facing data. This role will report to our Team Manager, R&D.
Why is this role so important?
we are a data-focused company, and data is the heart of our business.
As a big data engineer developer, you will work at the very core of the company, designing and implementing complex high scale systems to retrieve and analyze data from millions of digital users.
Your role as a big data engineer will give you the opportunity to use the most cutting-edge technologies and best practices to solve complex technical problems while demonstrating technical leadership.