Data Engineer – Databricks Experience: 3–6 Years Employment Type: Contract Project Duration: 3 Months Background: Bioinformatics / Life Sciences preferred Role Summary We are looking for a Data Engineer with strong Databricks experience to build and integrate clinical, biomarker and multi-omics datasets into a governed, analysis-ready data platform. The candidate should have exposure to Bioinformatics/Life Sciences data and experience developing scalable data pipelines on Databricks. Key Responsibilities • • Build Bronze → Silver → Gold data pipelines on Databricks. • Develop ingestion and transformation pipelines using PySpark, Python and SQL. • Build and maintain Delta Lake tables and analytical datasets. • Integrate and harmonize structured and semi-structured scientific datasets. • Implement data-quality, validation and reconciliation rules. • Develop incremental loading, exception handling and reprocessing mechanisms. • Support Unity Catalog, RBAC, metadata and data lineage. • Work with the Data Architect and Bioinformatics SME on domain-specific transformations and data models. • Develop Gold-layer curated datasets for analytics and downstream AI use cases. • Support testing, UAT, documentation and production readiness. Must Have • • 4+ years of Data Engineering experience. • Strong hands-on Databricks, PySpark, Python and SQL. • Spark, Delta Lake and Medallion Architecture. • ETL/ELT and data-pipeline development. • Data modelling and data-quality implementation. • Cloud object storage, preferably AWS S3. • Git and CI/CD experience. • Bioinformatics/Life Sciences data exposure. Preferred • • Experience with genomics, biomarker or multi-omics datasets. • Exposure to RNA-seq, WES/WGS, VCF, CNV or similar scientific datasets. • Unity Catalog and Databricks governance. • Databricks certification.