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Senior Data Engineer sits within the DSAD Platform and Architecture Team and is responsible for designing,\nbuilding, productionising and operating trusted data pipelines and reusable data products on the data platform using AWS and Databricks.\n\nExperience: Typically 6–10 years of relevant data or software engineering experience, including hands-on design and\noperation of production data pipelines and at least 2 years working with cloud-based data platforms.\n\n• Strong Python, PySpark and SQL capability, including distributed processing, complex transformations, query\noptimisation, debugging and automated testing.\n• Hands-on experience with Databricks, Apache Spark and Delta Lake for production-scale batch or streaming\ndata engineering.\n• Hands-on AWS data engineering experience with a relevant mix of S3, Glue, Lake Formation, IAM, KMS, Lambda,\nStep Functions, EventBridge, CloudWatch, Redshift and MSK/Kinesis.\n• Experience designing lakehouse or data-lake architectures, including layered data patterns, dimensional or\ndomain data modelling and reusable curated datasets.\n• Experience implementing incremental ingestion, change data capture, idempotency, late-arriving data handling,\nbackfills, replay and recovery.\n• Experience implementing data quality, schema validation, reconciliation, metadata and lineage as automated\nparts of production pipelines.\n• Experience with workflow orchestration, Git-based development, CI/CD, infrastructure as code such as\nTerraform, and environment promotion controls.\nSkills\nHealth Promotion, Distributed Processing, PySpark, Pipelines, Reconciliation, Infrastructure as Code (IaC), Relaxation, Data Quality Assurance, Data Lineage, PyTorch, Python, Workflow Orchestration, CI/CD, Anomaly Detection, Data Query, Pattern 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