Data Engineer
Group AMANA
Job description
About the role
Group AMANA is hiring a Data Engineer to design and deliver end-to-end data products for assigned business domains, covering the bronze, silver and gold layers, including dimensional and semantic models used for reporting and AI. The role also leads workstreams in the Synapse Analytics to Databricks migration and contributes reusable frameworks and patterns.
Key responsibilities
- Design and deliver data products across the bronze, silver and gold layers, including dimensional and semantic models for reporting and AI.
- Build robust ingestion from enterprise systems (Oracle Fusion, Hyperion, CMiC, SharePoint, Power Platform) using change data capture, incremental and API-based patterns.
- Lead the Synapse Analytics to Databricks migration: re-engineer pipelines, run parallel loads, reconcile results and prepare for cutover.
- Implement data quality frameworks, monitoring and reconciliation, and drive issues to resolution with data owners.
- Implement access control, lineage, classification and PDPL controls in Unity Catalog and Microsoft Purview, and partner with the Data Governance Office on certified datasets.
- Tune Spark and SQL workloads, own operational health (monitoring, alerting, incidents), and apply CI/CD, automated testing and DataOps via Git and Azure DevOps.
- Build AI-ready data products (feature tables, document and vector pipelines) with the Data Scientist and AI Engineer, and deliver Power BI semantic models with the Data Analyst.
- Mentor Data Engineers through pairing, design reviews and code review, and explain design choices to technical and business audiences.
Required profile
- 5+ years of hands-on data engineering experience, including at least 2 years with Databricks, Apache Spark and Delta Lake in production.
- Experience delivering end-to-end data products for one or more business domains.
- Experience integrating complex enterprise sources such as Oracle Fusion, SAP, Microsoft Dynamics or CMiC, including incremental and API-based extraction.
- Data quality and access controls implemented in practice with Unity Catalog, Microsoft Purview or equivalent.
- Strong SQL, Python and PySpark, with Git-based CI/CD delivery (Azure DevOps or equivalent).
- Excellent written and verbal communication across technical and business audiences.
Certifications
- Databricks Certified Data Engineer Associate or Microsoft Certified: Azure Databricks Data Engineer Associate (DP-750) within 6 months.
- Databricks Certified Data Engineer Professional within 12 months.
- Preferred: Databricks Certified Generative AI Engineer Associate, Microsoft Certified: Fabric Data Engineer Associate (DP-700), Fabric Analytics Engineer Associate (DP-600), or Azure Data Engineer Associate (DP-203, retired 2025).
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