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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 highly skilled and motivated Data Engineer & Analyst to join our dynamic team.
The ideal candidate will be a great team player that can lead and also be responsible for designing, developing, and maintaining robust data pipelines and analytical solutions to support our business objectives. This role requires a blend of engineering and analytical skills to ensure data integrity, optimize data workflows, and provide actionable insights. This role requires a deep understanding of financial data, system integration, and analytics to support strategic decision-making and regulatory compliance.
Your Day-to-Day
Design, develop, and maintain scalable data pipelines and ETL processes.
Collaborate with product, analysts, and other stakeholders to understand data
requirements and translate business needs into technical requirements.
Ensure data quality and integrity across various data sources.
Develop, maintain and own data models, schemas, and documentation.
Perform data analysis to identify trends, patterns, and insights.
Create and maintain dashboards and reports to support business decision-making.
Optimize database performance and troubleshoot issues.
Stay updated with the latest industry trends and best practices in data engineering and analytics.

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 Senior Data Scientist.
The Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing:
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

We are looking for a Data Scientist.
The Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing:
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

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

Required Data Engineer (Analytics)
Tel Aviv
As a Data Engineer, you will collaborate with various stakeholders to design, develop, and maintain data analytics solutions that enable informed business decisions. You will use the latest tools and technologies to ensure the data is accurate, timely, and actionable.
How is your day going to look, what will you be doing?
Develop data solutions in collaboration with data analysts, data scientists, product engineers, and product managers
Design and develop the infrastructure for ingesting and processing data in the analytics data warehouse
Design data analytics modeling solutions focused on business decision-making
Write robust ETL processes, handling a variety of structured and unstructured data sources
Ensure data quality, consistency, and governance across the analytics layer.

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.

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.