Sr. Data Engineer

Requirements:

• 5 to 8+ years of data engineering experience, with at least 3 years in cloud-based data lakehouse environments.
• Strong hands-on experience with Databricks Delta Lake, Workflows, Unity Catalogue, PySpark, and SQL notebooks.
• Solid dbt expertise: modelling patterns (staging intermediate mart), dbt testing frameworks, and CI/CD pipeline integration.
• Proficiency in Python and SQL for pipeline development and data transformation.
• Demonstrated experience building ADF (Azure Data Factory) pipelines for ingestion from relational databases, flat files, and API sources.
• Experience migrating legacy ETL tools (Alteryx, SAS, SSIS, Informatica, or equivalent) to modern, code-first, version-controlled pipelines.
• Familiarity with the Azure ecosystem: ADLS Gen2 Azure DevOps, Azure Key Vault, and Azure Active Directory / Entra ID.
• Experience designing and operating data pipelines in SOX-controlled or compliance-sensitive environments.
• Strong debugging and root-cause analysis skills for complex, multi-hop data pipelines.
• Effective written and verbal communication skills for cross-timezone collaboration with US-based architects and product managers.

Nice to Have:

• Exposure to Finance domain data in any of: ERP systems (Oracle, SAP, Workday), revenue data, planning and forecasting, accounting close cycles, tax compliance, or treasury and securitisation datasets.
• Databricks certifications (Data Engineer Associate or Professional).
• Experience with Delta Live Tables (DLT) for streaming or incremental ingestion patterns.
• Familiarity with Oracle ERP or Oracle EBPCS / BPM integration patterns.
• Experience with legacy-to-modern migrations from SAS, IBM TM1 SSAS multidimensional cubes, or on-premises SQL Server.
• GitLab CI/CD pipeline design for data workloads including automated regression test suites.
• Knowledge of T-Mobile DR COE reference architecture, TISS-310 data classification standards, or QSR cybersecurity requirements.
• Prior contribution to SEC regulatory reporting pipelines, SOX ITGC-controlled environments, or audit-ready data lineage design.