דרושים » דאטה » Senior Data Engineer

Required 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.

Data Infrastructure team is seeking a talented Data (Infra) Engineer to join us.
In this role, youll play a key part in shaping the strategic direction of our data infrastructure, driving high-impact projects across the organization. Youll lead the development of robust, scalable systems that support massive data flows, optimize cloud resource usage, and implement modern DevOps practices to improve system reliability, performance, and efficiency.
Were looking for someone who thrives in a fast-paced, collaborative environment and is passionate about building the infrastructure that powers cutting-edge data products.
In This Role, You Will:
Shape Data Architecture: Guide strategic decisions around data infrastructure components, collaborate on requirements, and own system design and implementation.
Lead Projects: Drive end-to-end delivery of high-scale, data-intensive projects from design through deployment and maintenance.
Optimize Cloud Costs: Monitor and fine-tune cloud usage to ensure cost-effective performance across environments.
Enhance Reliability: Build tools and processes to ensure data systems are efficient, reliable, and highly available.
Integrate DevOps Practices: Automate and streamline workflows with CI/CD, container orchestration, and Infrastructure as Code for scalable, reliable deployments.
Work with a Modern Stack: Azure, GCP, Kubernetes, ArgoCD, Jenkins, Databricks, Snowflake, Aerospike, Neo4J, Airflow, RDBMS, Spark-operator, Kafka, Microservices, Bash, Python, SQL.

Required Data Infrastructure Engineer
Tel Aviv
We are using technology to transform transportation around the world. From changing a single persons daily commute to reducing humanitys collective environmental footprint weve got huge goals.
As a Data Engineer, you will join a talented team of engineers, in charge of our core data infrastructure, while working closely with other engineering and data teams. You will lead the development of complex solutions, work on various cutting edge technologies, and be a critical part in our mission to shape the future of transportation, affecting tens of thousands of riders daily worldwide.
What Youll Do:
Design, build, and maintain scalable data platforms, pipelines, and solutions for data ingestion, processing and orchestration, leveraging Kubernetes, Airflow, Kafka and more.
Develop and manage cloud-based data solutions on AWS utilizing Infrastructure as Code (IaC) frameworks like Terraform or CloudFormation
Manage Snowflake environments, including database architecture, resource provisioning, and access control.
Ensure system reliability and observability with monitoring, logging, and alerting tools like Prometheus and CloudWatch.
Continuously optimize storage, compute, and data processing costs and performance.

If you share our love of sports and tech, you've got the passion and will to better the sports-tech and data industries - join the team. We are looking for a Data & AI Architect.
Responsibilities:
Build the foundations of modern data architecture, supporting real-time, high-scale (Big Data) sports data pipelines and ML/AI use cases, including Generative AI.
Map the companys data needs and lead the selection and implementation of key technologies across the stack: data lakes (e.g., Iceberg), databases, ETL/ELT tools, orchestrators, data quality and observability frameworks, and statistical/ML tools.
Design and build a cloud-native, cost-efficient, and scalable data infrastructure from scratch, capable of supporting rapid growth, high concurrency, and low-latency SLAs (e.g., 1-second delivery).
Lead design reviews and provide architectural guidance for all data solutions, including data engineering, analytics, and ML/data science workflows.
Set high standards for data quality, integrity, and observability. Design and implement processes and tools to monitor and proactively address issues like missing events, data delays, or integrity failures.
Collaborate cross-functionally with other architects, R&D, product, and innovation teams to ensure alignment between infrastructure, product goals, and real-world constraints.
Mentor engineers and promote best practices around data modeling, storage, streaming, and observability.
Stay up-to-date with industry trends, evaluate emerging data technologies, and lead POCs to assess new tools and frameworks especially in the domains of Big Data architecture, ML infrastructure, and Generative AI platforms.

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 Senior Data Engineer
In your role as a Data Engineer, you'll be actively engaged in the most fascinating and demanding projects for our clients. Handling high-scale operations, heavy traffic, stringent SLAs, and massive data volumes is just the starting point. Our leadership in the realms of Big Data, Streaming Data, and Complex Event Processing (CEP) stems from our adept use of cutting-edge, optimal technologies.
Responsibilities:
Apply software-engineering methods and best practices (Medallion Architecture) in Data Lake management, using tools like DBT.
Develop Data pipelines to ingest and transform data.
Manage and enhance orchestrated pipelines across company
Data Modeling: Developing data models to ensure efficient storage, retrieval, and processing of data, often involving schema design for NoSQL databases, data lakes, and data warehouses. This will also include catalogs of data.
Scalability: Ensuring that the big data architecture can scale horizontally to handle large volumes of data and high traffic loads.
Data Security: Implementing security measures to protect sensitive data, including encryption, access controls, and data masking.
Data Governance: Establishing data governance policies to ensure data quality, compliance with regulations, and data lineage.

We're looking for highly talented, experienced, passionate, and data-driven DataOps/ Analytics Engineer.
This role bridges the gap between data engineering and analytics teams, focusing on the orchestration, maintenance, and optimization of our analytics infrastructure.
Responsibilities:
Orchestration Pipelines: Design and manage data orchestration pipelines using Dagster.
Data Modeling: Develop and enforce guidelines and standards for data modeling in dbt, ensuring comprehensive documentation and adherence to best practices.
Data Warehousing: Maintain and optimize our BigQuery data warehouse, focusing on performance monitoring, cost management, and data quality.
Data Catalog Management: Enhance and maintain our Data Hub data catalog.
CI/CD Management: Implement CI/CD processes, orchestration pipelines, and automated data quality monitoring to streamline workflows and reduce manual interventions.
Infrastructure Management: Utilize Kubernetes for hosting, and manage associated tools such as Elasticsearch and Grafana.
Data Quality: Implement and monitor data quality processes, including alerting and reporting mechanisms.
Development Workflow Optimization: Improve and maintain development workflows to ensure efficient and seamless data product delivery.
Collaborative Design: Work alongside business users and data analysts to design and build data models that enhance data discovery and analyses.
Standards and Best Practices: Contribute to internal standards for style, maintainability, and best practices for a high-scale data infrastructure.
Documentation and Scalability: Maintain documentation, manage technical debt, and ensure scalability of infrastructure.

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

Data Engineer
We're hiring an experienced Data Engineer to join our growing team of analytics experts in order to help & lead the build-out of our data integration and pipeline processes, tools and platform.
The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
The right candidate must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our companys data architecture to support our next generation of products and data initiatives.
In this role, you will be responsible for:
Create ELT/Streaming processes and SQL queries to bring data to/from the data warehouse and other data sources.
Establish scalable, efficient, automated processes for large-scale data analyses.
Support the development of performance dashboards & data sets that will generate the right insight.
Work with business owners and partners to build data sets that answer their specific business questions.
Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making across the organization.
Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
Own the data lake pipelines, maintenance, improvements and schema.

Required Staff Algo Data Engineer
Realize your potential by joining the leading performance-driven advertising company!
As a Staff Algo Data Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
About Algo platform:
The objective of the algo platform group is to own the existing algo platform (including health, stability, productivity and enablement), to facilitate and be involved in new platform experimentation within the algo craft and lead the platformization of the parts which should graduate into production scale. This includes support of ongoing ML projects while ensuring smooth operations and infrastructure reliability, owning a full set of capabilities, design and planning, implementation and production care.
The group has deep ties with both the algo craft as well as the infra group. The group reports to the infra department and has a dotted line reporting to the algo craft leadership.
The group serves as the professional authority when it comes to ML engineering and ML ops, serves as a focal point in a multidisciplinary team of algorithm researchers, product managers, and engineers and works with the most senior talent within the algo craft in order to achieve ML excellence.
How youll make an impact:
As a Staff Algo Data Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet
Our tech stack:
Java, Python, TensorFlow, Spark, Kafka, Cassandra, HDFS, vespa.ai, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes, Docker, git and Jenkins.