Job Title: Senior Data Engineer Reports To : Principal Data Engineer Department : Digital - Elysia Direct Reports : As required (not immediately). Position Type: Permanent Location: Kidlington, Oxford or Central London location available Onsite policy: Hybrid, 3 days on / 2 days off working offered Role Purpose: In this “Senior Data Engineer” role within the Elysia Battery Intelligence, you will lead the design and implementation of scalable, production-grade data pipelines across a range of sources such as Automotive, Stationary Storage (ESS), Battery Testing Facilities, and R&D environments. You will take ownership of architectural decisions, define and enforce data modelling and engineering standards, and mentor junior engineers in best practices. Leveraging tools like AWS, Snowflake, Dagster, and Python, you’ll drive the delivery of automated, secure, and observable pipelines that support mission-critical analytics and product features. This role is pivotal in aligning engineering workflows with scientific, regulatory, and business needs, ensuring high data fidelity, pipeline efficiency, and operational resilience. Key Responsibilities: Lead the design and implementation of robust data pipelines utilising python and SQL Architect scalable ingestion strategies for high-volume telemetry and time-series data. Data quality and monitoring: Implement robust data quality checks and monitoring systems to ensure the accuracy, consistency, and reliability of data. Define data modelling standards and enforce schema governance in database solutions. Collaborate with product, analytics, and cloud teams to define SLAs, metrics, and data contracts. Mentor and support junior data engineers via code reviews, pairing, and design sessions. Identify inefficient data processes, engineer solutions to improve operational efficiencies, performance, and scalability, and create accessible data models supporting analytics business functions. Actively participate in improving customer onboarding data pipelines and ensure data integrity and security. Collaborate with cross-functional teams to understand data requirements and ensure data pipelines meet business needs. Contribute to roadmap planning, tool evaluation, and architectural decisions. Qualifications & Experience: Master’s degree in a relevant field (Engineering, Physics, Mathematics, Computer Science, or similar) or equivalent experience. 5 years’ experience in data engineering on cloud-based systems Strong expertise in Python and SQL for data engineering Strong skills in data modelling and ETL/ELT processes Experience with modern data warehouse platforms (e.g., Snowflake, BigQuery): Experience with RDBMS or time-series databases Experience with streaming data sources such as Kafka or MQTT or AWS Kinesis Experience in coding best practices, and source code management. Experience in data engineering and data science-related modules in Python ecosystem. Strong experience in version control frameworks (GitHub/GitLab) and CI/CD workflows Ability to communicate the ideas/solutions to colleagues and customers. Ability to stay up to date with industry trends and emerging technologies. Ability to present the solutions to management and stakeholders. Ability to work both independently and collaboratively. Beneficial: Experience using modern data orchestration tools (e.g. Dagster, Airflow, Prefect, AiiDA). Experience with AWS services (EC2, ECS, Lambda, Glue, Athena, DynamoDB) Experience in creating/managing containerized applications. This job description is not exhaustive, and the job holder will be required to carry out from time-to-time tasks in addition to the above that will be both reasonable and within their capabilities.