דרושים » תוכנה » Data Engineer

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 the leader in hybrid-cloud security posture management, using the attackers perspective to find and remediate critical attack paths across on-premises and multi-cloud networks. we are looking for a talented Senior data Engineer Join a core team of experts responsible for developing innovative cyber-attack techniques for Cloud-based environments (AWS, Azure, GCP, Kubernetes) that integrate into our fully automated attack simulation. About the Role:We are seeking an experienced Senior data Engineer to join our dynamic data team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure, ensuring the availability, reliability, and quality of our data. This role requires strong technical expertise, problem-solving skills, and the ability to collaborate across teams to deliver data -driven solutions.Key Responsibilities:
* Design, implement, and maintain robust, scalable, and high-performance data pipelines and ETL processes.
* Develop and optimize data models, schemas, and Storage solutions to support analytics and Machine Learning initiatives.
* Collaborate with software engineers and product managers to understand data requirements and deliver high-quality solutions.
* Ensure data quality, integrity, and governance across multiple sources and systems.
* Monitor and troubleshoot data workflows, resolving performance and reliability issues.
* Evaluate and implement new data technologies and frameworks to improve the data platform.
* Document processes, best practices, and data architecture.
* Mentor junior data engineers and contribute to team knowledge sharing.

We are looking for a Senior Data Engineer to join our Platform group in the Data Infrastructure team.
Youll work hands-on to design and deliver data pipelines, distributed storage, and streaming services that keep our companys data platform performant and reliable. As a senior individual contributor you will lead complex projects within the team, raise the bar on engineering best-practices, and mentor mid-level engineers while collaborating closely with product, DevOps and analytics stakeholders.
Code & ship production-grade services, pipelines and data models that meet performance, reliability and security goals
Lead design and delivery of team-level projects from RFC through rollout and operational hand-off
Improve system observability, testing and incident response processes for the data stack
Partner with Staff Engineers and Tech Leads on architecture reviews and platform-wide standards
Mentor junior and mid-level engineers, fostering a culture of quality, ownership and continuous improvement
Stay current with evolving data-engineering tools and bring pragmatic innovations into the team.

We are looking for a hands-on data infrastructure and platform engineer with proven leadership skills to lead and evolve our self-service data platform that powers petabyte-scale batch and streaming, near-real-time analytics, experimentation, and the feature platform. Youll guide an already excellent team of senior engineers, own reliability and cost efficiency, and be the focal point for pivotal, company-wide data initiatives- feature platform, lakehouse, and streaming.
Own the lakehouse backbone: Mature Iceberg at high scalepartitioning, compaction, retention, metadataand extend our IcebergManager in-house product to automate the lakehouse management in a self serve fashion.
Unify online/offline for features: Drive Flink adoption and patterns that keep features consistent and low-latency for experimentation and production.
Make self-serve real: Build golden paths, templates, and guardrails so product/analytics/DS engineers can move fast safely.
Run multi-tenant compute efficiently: EMR on EKS powered by Karpenter on Spot instances; right-size Trino/Spark/Druid for performance and cost.
Cross-cloud interoperability: BigQuery + BigLake/Iceberg interop where it makes sense (analytics, experimentation, partnership).
What you'll be doing
Leading a senior Data Platform team: setting clear objectives, unblocking execution, and raising the engineering bar.
Owning SLOs, on-call, incident response, and postmortems for core data services.
Designing and operating EMR on EKS capacity profiles, autoscaling policies, and multi-tenant isolation.
Tuning Trino (memory/spill, CBO, catalogs), Spark/Structured Streaming jobs, and Druid ingestion/compaction for sub-second analytics.
Extending Flink patterns for the feature platform (state backends, checkpointing, watermarks, backfills).
Driving FinOps work: CUR-based attribution, S3 Inventory-driven retention/compaction, Reservations/Savings Plans strategy, OpenCost visibility.
Partnering with product engineering, analytics, and data science & ML engineers on roadmap, schema evolution, and data product SLAs.
Leveling up observability (Prometheus/VictoriaMetrics/Grafana), data quality checks, and platform self-service tooling.

Were looking for a hands-on leader to take ownership of our data and analytics landsape.
This isnt a pure management role we need someone who can roll up their sleeves, dive into AWS environments, and still have the strategic view to guide a growing data team.
The ideal candidate combines strong technical expertise in data engineering and analytics with a solid understanding and genuine passion for Artificial Intelligence (AI) including how AI can enhance data-driven decision-making and operational efficiency in the financial domain.
In this position youll:
Shape the companys overall data strategy and decide how we store, move, and use data across the business.
Lead a small but growing group of engineers, analysts, and BI specialists, making sure they have the right tools and direction.
Stay close to the technology designing and reviewing data pipelines, checking performance, and being the go-to person for AWS data solutions like Redshift, Glue, Athena, S3, and others.
Work with business leaders (finance, risk, compliance) to turn their questions into clear, data-driven answers.
Identify opportunities to integrate AI/ML into data workflows and business processes.
Establish best practices for data governance, quality, and security in a financial services org.
Drive automation and efficiency through modern data and AI tools

Join a team of skilled data engineers building sophisticated data pipelines connecting a variety of systems through streaming technologies, cloud services, and microservices.

As a Senior Data Engineer, youll play a key role in shaping the infrastructure powering our data ecosystem. Youll design, build, and maintain scalable data pipelines and automation processes, enabling reliable, efficient, and observable systems.

This is a hands-on role that combines infrastructure, data, and DevOps expertise - perfect for someone who thrives on learning new technologies, leading initiatives, and driving excellence in system design and delivery.

Responsibilities:
Design and maintain robust infrastructure for large-scale data processing and streaming systems.
Develop automation and deployment processes using CI/CD pipelines.
Build and operate Kubernetes-based environments and containerized workloads.
Collaborate with data engineers to optimize performance, cost, and reliability of data platforms.
Design and develop REST-API microservices.
Troubleshoot and resolve complex issues in production and staging environments.
Drive initiatives that enhance observability, scalability, and developer productivity.
Lead by example - share knowledge, mentor teammates, and promote technical best practices.

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.
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.

As a Senior Algo Data Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Senior Algo Data 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.

Were looking for an organized and collaborative BI Developer to lead complex analytics initiatives and help shape our companys data foundation. Youll work closely with data engineers and product-aligned analysts to design scalable data models, build enterprise dashboards, and drive consistent, data-driven decision-making across teams.
Key Responsibilities:
Write and optimize complex SQL queries for large-scale datasets in Athena and Redshift.
Design and build Looker dashboards and LookML models from scratch.
Develop and maintain a shared aggregation layer to support analytics and reporting across products.
Automate and schedule data workflows in Airflow for reliable, efficient data delivery.
Collaborate with data engineers on ETL/ELT design, data modeling, and schema optimization.
Lead and mentor product-focused analysts to ensure high analytical standards and consistency.
Communicate insights clearly to technical and non-technical stakeholders.

Provide the direction of our data architecture. Determine the right tools for the right jobs. We collaborate on the requirements and then you call the shots on what gets built.
Manage end-to-end execution of high-performance, large-scale data-driven projects, including design, implementation, and ongoing maintenance.
Optimize and monitor the team-related cloud costs.
Design and construct monitoring tools to ensure the efficiency and reliability of data processes.
Implement CI/CD for Data Workflows