delivering data engineering solutions on cloud platforms, preferably Oracle OCI, AWS, or Azure Proficient in Python and workflow orchestration tools such as Airflow or Prefect Expert in data modeling, ETL, and SQL Experience with real-time analytics from telemetry and event-based streaming (e.g., Kafka) Experience managing operational data stores with high availability, performance, and scalability Expertise in data lakes More ❯
Oxford, Oxfordshire, United Kingdom Hybrid / WFH Options
Elsevier
Deploy and govern modern data stack technologies (e.g., Snowflake, Airflow, DBT, Fivetran, Airbyte, Tableau, Sisense, AWS, GitHub, Terraform, Docker) at enterprise scale for data engineering workloads. Develop deployable, reusable ETL/ELT solutions using Python, advanced SQL, and Jinja for data pipelines and stored procedures. Demonstrate applied understanding of SDLC best practices and contribute to the maturity of SDLC, DataOps More ❯
development and deployment Evaluate and adopt new data technologies Collaborate with scientists, researchers, and operational teams Qualifications & Experience: Extensive Python programming experience in enterprise environments Knowledge of data modeling, ETL, data warehousing, and SQL Cloud computing experience Strong communication skills Innovative mindset and ability to solve challenges creatively Ability to work in a fast-paced, startup-like environment Nice to More ❯
