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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
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 visually 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
Influence product and cross-functional teams to identify data opportunities to drive impact.

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 aspectsensuring 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.

Req ID: 20718

we are looking for a 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 are looking for a Senior Data Engineer.
As a Senior Data Engineer, youll be more than just a coder - youll be the architect of our data ecosystem. Were looking for someone who can design scalable, future-proof data pipelines and connect the dots between DevOps, backend engineers, data scientists, and analysts.
Youll lead the design, build, and optimization of our data infrastructure, from real-time ingestion to supporting machine learning operations. Every choice you make will be data-driven and cost-conscious, ensuring efficiency and impact across the company.
Beyond engineering, youll be a strategic partner and problem-solver, sometimes diving into advanced analysis or data science tasks. Your work will directly shape how we deliver innovative solutions and support our growth at scale.
Responsibilities:
Design and Build Data Pipelines: Architect, build, and maintain our end-to-end data pipeline infrastructure to ensure it is scalable, reliable, and efficient.
Optimize Data Infrastructure: Manage and improve the performance and cost-effectiveness of our data systems, with a specific focus on optimizing pipelines and usage within our Snowflake data warehouse. This includes implementing FinOps best practices to monitor, analyze, and control our data-related cloud costs.
Enable Machine Learning Operations (MLOps): Develop the foundational infrastructure to streamline the deployment, management, and monitoring of our machine learning models.
Support Data Quality: Optimize ETL processes to handle large volumes of data while ensuring data quality and integrity across all our data sources.
Collaborate and Support: Work closely with data analysts and data scientists to support complex analysis, build robust data models, and contribute to the development of data governance policies.

Required Senior Data Engineer
The opportunity
Join our dynamic Data & ML Engineering team in iAds and play a pivotal role in driving data solutions that empower data science, finance, analytics, and R&D teams. As an Experienced Data Engineer, you'll work with cutting-edge technologies to design scalable pipelines, ensure data quality, and process billions of data points into actionable insights.
Success Indicators:
In the short term, success means delivering reliable, high-performance data pipelines and ensuring data quality across the product. Long-term, you'll be instrumental in optimizing workflows, enabling self-serve analytics platforms, and supporting strategic decisions through impactful data solutions.
Impact:
Your work will directly fuel business decisions, improve data accessibility and reliability, and contribute to the team's ability to handle massive-scale data challenges. You'll help shape the future of data engineering within a global, fast-paced environment.
Benefits and Opportunities
You'll collaborate with talented, passionate teammates, work on exciting projects with cutting-edge technologies, and have opportunities for professional growth. Competitive compensation, comprehensive benefits, and an inclusive culture make this role a chance to thrive and make a global impact.
What you'll be doing
Designing and developing scalable data pipelines and ETL processes to process massive amounts of structured and unstructured data.
Collaborating with cross-functional teams (data science, finance, analytics, and R&D) to deliver actionable data solutions tailored to their needs.
Building and maintaining tools and frameworks to monitor and improve data quality across the product.
Providing tools and insights that empower product teams with real-time analytics and data-driven decision-making capabilities.
Optimizing data workflows and architectures for performance, scalability, and cost efficiency using cutting-edge technologies like Apache Spark and Flink.

As a customer-centric tech company, we created an insurance experience that is smart, instant, and delightful.
youll be working with a group of like-minded makers, who get a kick out of moving fast and delivering great products. We surround ourselves with some of the smartest, most motivated, creative people who are filled with positive energy and good karma.
Unlike most publicly traded companies, were nimble and efficient. We take pride in the fact that we still think and operate like a startup. We dont care much about titles and hierarchy and instead focus on innovation, bold moves, and challenging the status quo.
Were built as a lean, data-driven organization that relies on a common understating of objectives and goals to provide teams with autonomy and ownership. We dont like spending our days in meetings and we skip committees altogether. theres no such thing as going over someones head. We have zero tolerance for bureaucracy, office politics, and lean-back personalities.

As a Public Benefit Corporation and a certified B-Corp, we deliver environmental and social impact using our products and tech. Through our Giveback program, we partner with organizations such as the ACLU, New Story, The Humane Society, Malala Fund, American Red Cross, 360.org, charity: water, and dozens of others, and have donated millions towards reforestation, education, animal rights, LGBTQ+ causes, access to water, and more.
Were looking for an experienced Data Engineer to join our DataWarehouse team in TLV.

In this role, you will play a pivotal role in the Data Platform organization, leading the design, development, and maintenance of our data warehouse. In your day-to-day, youll work on data models and Backend BI solutions that empower stakeholders across the company and contribute to informed decision-making processes all while leveraging your extensive experience in business intelligence.

This is an excellent opportunity to be part of establishing state-of-the-art data stack, implementing cutting-edge technologies in a cloud environment.
In this role youll
Lead the design and development of scalable and efficient data warehouse and BI solutions that align with organizational goals and requirements
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 the semantic layer
Develop processes to enforce schema evaluation, cover anomaly detection, and monitor data completeness and freshness
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 with Data Infra Engineers, Developers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers

we are looking for a Data Engineer to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless company ronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
In this role, you will be responsible for:
Designing, building, and maintaining scalable data pipeline architectures
Developing ETL processes to integrate data from multiple sources
Creating and optimizing data models for efficient storage and retrieval
Implementing data quality controls and monitoring systems
Collaborating with data scientists and analysts to deliver data solutions
Building and maintaining data warehouses and data lakes
Performing in-depth data analysis and providing insights to stakeholders
Taking full ownership of data quality, documentation, and governance processes
Building and maintaining comprehensive reports and dashboards
Ensuring data security and regulatory compliance.

Were looking for a Data Engineer to join our data warehouse team and play a pivotal role in driving data solutions that empower data science, GTM, finance, analytics and R&D teams.

If youre passionate about exploring and exposing product and business data to stakeholders across and beyond, wed love to hear from you.



What youll do:

Lead the design and development of scalable and efficient data warehouse and BI solutions that align with organizational goals and requirements.
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 shared data warehouse.
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency.
Collaborate with cross-functional teams (product, finance, analytics, and R&D) to deliver actionable data solutions tailored to their needs.

We are looking for a highly skilled and experienced Data Engineering Team Lead to join our dynamic team in Tel Aviv.
In this pivotal role, you will oversee the design, development, and optimization of our infrastructure, ensuring efficient flow and quality to support data-driven decision-making across the organization. You will lead a team of backend developers and data engineers, collaborate with cross-functional teams, and drive initiatives to enhance our data collection and data pipeline capabilities.
Key Responsibilities:
Lead and oversee a team of BackEnd and Data Engineers, mentor the team members, fostering skill development and professional growth
Establish and enforce data quality standards, implementing processes for data accuracy, reconciliation, and consistency.
Oversee the design and implementation of robust ETL processes to ensure accurate and timely data integration from various sources.
Collaborate across the business with various stakeholders, such as the CTO, Data Analysts and Product Managers to deliver impactful solutions
Continuously monitor and optimize system flows for performance, scalability, and cost-efficiency.

We are growing and are looking for a Senior Data Infra Engineer
who value personal and career growth, team-work, and winning!
What your day will look like:
Design, plan, and build all aspects of the platforms data, machine learning (ML) pipelines, and infrastructure.
Build and optimize an AWS-based Data Lake using best practices in cloud architecture, data partitioning, metadata management, and security to support enterprise-scale data operations.
Collaborate with engineers, data analysts, data scientists, and other stakeholders to understand data needs.
Solve challenging data integration problems, utilizing optimal ETL/ELT patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
Lead end-to-end data projects from infrastructure design to production monitoring.