Senior Data Engineer

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Key Responsibilities • Data Pipeline Architecture and Delivery: Lead the design and implementation of maintainable batch and streaming pipelines that ingest, validate, transform and publish structured, semi-structured and unstructured data across AWS and Databricks. • Lakehouse and Data Product Engineering: Design Bronze, Silver and Gold data layers using Delta Lake or equivalent patterns; develop reusable domain data models, curated datasets and data products with explicit ownership, definitions and service expectations. • Source Integration and Incremental Processing: Implement reliable ingestion from databases, files, APIs and event streams using full-load, incremental, change-data-capture and replayable processing patterns appropriate to each source. • Data Quality and Contracts: Establish schema enforcement, data contracts, automated validation, reconciliation and anomaly checks covering completeness, validity, consistency, uniqueness, timeliness and referential integrity. • Orchestration and Deployment Automation: Build parameterised workflows using Databricks Workflows or Lakeflow and relevant AWS services; integrate automated testing, nfrastructure as code and CI/CD controls across development, test and production environments. • Metadata, Lineage and Governance: Implement technical metadata, business definitions, end-to-end lineage, classification, ownership and access controls using Unity Catalog, AWS Glue Data Catalog, Lake Formation or approved platform capabiliti

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