Expertise expected –

- Solid Data Engineer experience in enterprise environments, with hands-on OneSource 2.0 / OneHouse &
- DTU practice –
- Databricks (Spark/SQL, Delta Lake) mandatory
- ADF / Azure stack; exposure to Snowflake / Informatica a plus –
- Solid data modelling for analytics (facts, dimensions, derived metrics) and medallion architecture –
- Comfortable with config-as-code / GitHub / CI-CD working model;

experience integrating ERP / Finance / Commercial data (e.g. SAP) Leadership positioning (technical, not managerial) –
- Recognized technical reference within the squad; able to coach juniors and justify design choices among competing alternatives –
- Operates under the guidance of the Chapter Manager — no people-management, capacity or standard-setting accountability

Technical leadership at squad level –
- Act as the technical reference for the squad’s data engineering work on OneSource 2.0 –
- Guide solution build within guardrails; drive design and code quality through peer review –
- Mentor and upskill junior data engineers; support estimation and technical planning –
- Contribute to Engineering Decision Records (EDRs) for implementation-level decisions Data ingestion (config-driven) –
- Configure ingestion using the OneHouse metadata-driven framework: create/modify JSON configuration files (ingestion, Bronze) and deploy via GitHub / GitOps / CI-CD –
- Onboard sources (SAP/DB2, files, Snowflake,



external push/pull) into OneHouse, ensuring reliability, completeness and lineage Transformation & data modelling (core value) –
- Build Silver (cleaned, harmonized, modelled) and Gold (business aggregations / data products) datasets implementing business KPIs –
- Apply and enrich reusable logic from the Transformations Library; document and version it –
- Translate KPI definitions into scalable transformations aligned with domain data models Platform engineering within DTUs –
- Develop within DTUs using Databricks (Spark/SQL/Delta Lake) and, where relevant, ADF, Snowflake or Informatica –
- Structure data across Bronze / Silver / Gold; optimize performance, cost (FinOps) and scalability –
- Apply best practices for CI/CD, IaC, monitoring and data quality checks Governance & data products –
- Verify integrity of ingested data and entities in Unity Catalog; respect GBDO / Data Owner validation and security-by-design –
- Ensure only OneHouse-stored, catalogued data is published as shareable, certified data products (SSOT)

Building governed Bronze/Silver/Gold data products in OneHouse and DTUs, and coaching junior engineers — while reporting to the L8 Chapter Manager. “Lead” reflects technical seniority, not a management layer, keeping the role cleanly one level below the Chapter Manager in the chapter structure

📌 IT&Data Engineer (Hyderabad)
🏢 Infosys
📍 Hyderabad