Job Description

Responsibilities :

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)

Additional Responsibilities:

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

Technical and Professional Requirements:

Expertise expected - Strong 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