SR. DATA ENGINEER
Bengaluru · Senior
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HIGH
Our tracked job listings for TE Connectivity show strong recent activity.
First 72 hours
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Job description
Job Overview
- Build declarative pipelines (Databricks Lakeflow / DLT) on Medallion Architecture (Bronze → Silver → Gold), delivering governed, audit-ready data products with Unity Catalog lineage, access controls, and CI/CD (Asset Bundles, GitHub Actions).
- Able to decode SAP ABAP programs (Z-reports, Transaction codes) into modern Databricks pipelines and orchestrate pipelines via Databricks Workflows.
- Build production grade, reliable ETL/ELT processes using Python / PySpark transformations notebooks in Databricks / DBT Tool to transform, validate and publish data from multiple sources or bronze layers.
- Design optimized, scalable and well documented Gold Layers and semantic models (Direct Lake, star-schema, RLS, incremental refresh) for high-performance finance reporting in Microsoft Fabric / Sigma Computing / Databricks.
- Build AI Integrated Insights on curated Gold-layer finance datasets to enable natural-language analytics for Finance Users.
- Act as strategic consultants to senior finance stakeholders like elicit requirements, frame problems, build business cases, and produce BRDs, dependency matrix and required documentation.
- Establish architecture standards, perform RCA on data and platform issues, close lineage / KPI gaps, and drive structural fixes.
- Mentor engineers / BI analysts and Finance users on copilots and promoting best practices.
What your background should look like:
- 6-8 years of experience in Data engineering.
- Build declarative pipelines (Databricks Lakeflow / DLT) on Medallion Architecture (Bronze → Silver → Gold), delivering governed, audit-ready data products with Unity Catalog lineage, access controls, and CI/CD (Asset Bundles, GitHub Actions).
- Able to decode SAP ABAP programs (Z-reports, Transaction codes) into modern Databricks pipelines and orchestrate pipelines via Databricks Workflows.
- Build production grade, reliable ETL/ELT processes using Python / PySpark transformations notebooks in Databricks / DBT Tool to transform, validate and publish data from multiple sources or bronze layers.
- Design optimized, scalable and well documented Gold Layers and semantic models (Direct Lake, star-schema, RLS, incremental refresh) for high-performance finance reporting in Microsoft Fabric / Sigma Computing / Databricks.
- Build AI Integrated Insights on curated Gold-layer finance datasets to enable natural-language analytics for Finance Users.
- Act as strategic consultants to senior finance stakeholders like elicit requirements, frame problems, build business cases, and produce BRDs, dependency matrix and required documentation.
- Establish architecture standards, perform RCA on data and platform issues, close lineage / KPI gaps, and drive structural fixes.
- Mentor engineers / BI analysts and Finance users on copilots and promoting best practices.
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