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Planet (satellite imaging company) is hiring a Senior Data Engineer in Arlington, VA (hybrid, 3 days/week in office) to architect and build enterprise-scale, cloud-native data pipelines powering customer-facing global monitoring products for Defense and Intelligence customers. Core stack: Python, SQL, GCP, GitLab CI, Docker, Kubernetes.
Senior Data Analyst at 9amHealth acting as the analytics partner to Customer Success: owning client-facing reporting (QBRs, dashboards, ad hoc analyses) end to end. Core stack is Looker/LookML, expert-level SQL (Redshift, Aurora/MySQL, Athena) and Python, with heavy use of AI tools like Claude, Copilot, and Cursor to accelerate analytics work.
Gritt Robotics is hiring an ML Infrastructure Engineer to architect cloud-based AI training, data-ingestion, evaluation, and CI/CD pipelines for its autonomous construction robots, optimizing GPU and I/O performance using Python, PyTorch, Docker, Kubernetes, and Airflow on AWS/GCP/Azure. Onsite in the SF Bay Area.
Senior engineer on Datadog's Husky Storage team, building the petabyte-scale distributed columnar event store behind products like Logs, RUM, and APM. Day-to-day work spans migrating storage to open formats (Parquet, Arrow, DataFusion, Iceberg), cost-reduction and tiering projects, and operating large-scale distributed systems.
Mid-level data engineer joining the Vehicle Data API Team in Volkswagen Financial Services' European D&A Hub in Warsaw, building and operating AWS cloud APIs, microservices, and data ingestion/processing pipelines for group-wide vehicle data. Core stack: Python, AWS, MySQL, Docker, Terraform, Datadog, CI/CD, with a small on-call rotation and hybrid 3-days-in-office work.
Senior Cloud Data Engineer on VWFS's Vehicle Data API Team in Warsaw, developing and operating cloud-native APIs, microservices, and data pipelines that deliver vehicle data across the group. Daily work spans Python on AWS, Terraform, Docker/ECS/EKS, data quality automation, and light on-call duty (up to 12 days/year).
Semi-senior Data Engineer who designs, builds, and maintains batch and streaming data pipelines on Google Cloud Platform: ingesting data into BigQuery, orchestrating flows with Cloud Composer (Airflow), transforming with Dataflow/dbt, and ensuring data quality, governance, cost optimization, and CI/CD practices.
For over four decades, PAR Technology Corporation (NYSE: PAR) has been a leader in restaurant technology, empowering brands worldwide to create lasting connections with their guests. Our innovative solutions and…
Data engineer on Sofidel's corporate IT team, designing and maintaining ETL/ELT pipelines and data models that collect, transform and serve data from business and manufacturing systems for reporting, analytics and AI solutions, using SQL, Python, Spark/Databricks, Airflow and cloud data platforms.
Data engineer at a research foundation supporting digitalization of the paper-making industry (tissue/hygiene), splitting time between an industrial partner's site and Start Attractor. Day to day: designing and maintaining ETL/ELT pipelines and the data platform using SQL, Python, Spark/Databricks, Airflow and cloud services, also feeding AI/agentic use cases.
Senior backend engineer at a climate-tech startup building the platform that turns farm and food supply-chain data into decisions. Day to day: build services, APIs, ingestion pipelines, and data processing workflows in TypeScript/Node.js and Python, with SQL, cloud infrastructure, and IaC.
Lead Azure Data Engineer on a 12+12+12-month contract with a Commonwealth Government agency in Canberra (hybrid). You design and build ETL/ELT ingest and transformation pipelines and frameworks using Azure, Databricks, Spark and Data Factory, prepare Parquet/Delta data for analytics and AI, develop Power BI visualisations, and mentor other data engineers.
Senior Data Engineer on Manulife's North American Retirement team: designs, builds, and monitors cloud-based data pipelines, models, and lakehouse platforms, ensures data quality, and supports analytics and ML use cases. Core stack is Azure (Data Factory, ADLS, Databricks), SQL, PySpark, and Git.
Platform engineer at Sweden's central bank (Riksbanken) building and maintaining its in-house data and AI platforms on Kubernetes, S3 object storage and Python — mostly on-prem with some Azure. Day to day: automating CI/CD, running containerized services, improving stability, and driving platform adoption with business users.
Build and scale data pipelines that tag petabytes of autonomous-truck logs, turning raw sensor data into curated driving scenarios for ML and simulation teams using Python, Databricks, AWS, and CI/CD.
Builds and maintains the pipeline that records, curates, and prepares multimodal robot datasets (cameras, joint encoders, force-torque, teleoperation) for foundation-model training at Agile Robots. Core stack: ROS 2 and Python, with sensor sync, dataset schemas (Parquet/Zarr/HDF5), and synthetic data from simulation.
Hands-on engineering manager (staff level) building and leading a new Data Platform team at Motional to accelerate ML dataset generation and the data warehouse stack for autonomous vehicles. Core technologies include Python, AWS/GCP cloud, Parquet/Iceberg/Lance storage formats, and orchestration frameworks like Airflow.
Senior data engineer in Dubai owning production data pipelines end to end: building batch ETL/ELT and a lakehouse with dbt, Airflow, Spark/PySpark, Iceberg and Dremio on S3 storage, using Python and advanced SQL, plus hands-on work with NoSQL stores like Redis, MongoDB, Cassandra and Elasticsearch. Requires 10+ years of data engineering experience; on-site.
Middle SDET role testing a distributed data platform's query engine, APIs, and backend services across major clouds, ensuring correctness, performance, and reliability for enterprise AI and analytics workloads.
Platform Engineer on the data & AI platform teams at Sweden's central bank, maintaining and developing Riksbanken's in-house data/AI platform (Kubernetes, S3 object storage, Python, mainly on-prem with some Azure) — automating CI/CD and drift, running containerized services, and driving platform adoption with business users.
