Responsibilities
- Establish the enterprise data architecture by owning conceptual, logical, and physical data models for analytical and operational data platforms, including source-aligned, integrated, and consumption-ready layers.
- Design and maintain a meta-model that captures entities, relationships, business definitions, ownership, lineage, sensitivity classifications, and SLAs, ensuring integration with tooling rather than static documentation.
- Architect medallion Delta Lake patterns on Databricks, defining standards for partitioning, clustering, schema evolution, slowly changing dimensions, and historical reproducibility.
- Write PySpark, SQL, and Delta Lake code, build reference implementations, prototype patterns, review pull requests, and personally model critical domains without delegating all details.
- Set patterns for ingestion using Informatica Data Management Cloud and direct Databricks pipelines, including CDC, batch, streaming, and API-based sourcing from SaaS products and third-party systems.
- Collaborate with data governance, security, and compliance leaders to operationalize cataloging, lineage, classification, masking, and access controls across Unity Catalog, IDMC, and related tools.
- Establish standards, naming conventions, and review processes for the Data Engineering team, coaching engineers on dimensional modeling, Data Vault, and other techniques as appropriate.
- Work closely with Product, Engineering, Analytics, ML, Finance, Risk, and Customer-facing teams to translate business requirements into durable data designs.
- Identify gaps in tooling, capability, and skills; propose investments; and drive multi-quarter initiatives to improve data usage.
