Senior Data Engineer
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Requirements
• · 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. • · 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.
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.
Benefits
• Equity options mentioned as part of the benefits package • Paid time off (PTO) is included with a generous amount and flexibility for personal days/holidays • Comprehensive insurance coverage provided to employees, including health, dental, vision, life, disability income protection plans. This includes employer contributions towards premiums where applicable • Perks such as free meals are offered during work hours at the office or designated cafeteria areas for remote workers if they choose onsite dining options when in Kidlington/Oxford location