Enterprise Data Strategy Leader

4 days ago

Pune, Maharashtra, India beBeeData Full time ₹ 50,00,000 - ₹ 60,00,000
Senior Data Architect Position

A leading IT organization is seeking an experienced Senior Data Architect to spearhead the design and implementation of a cross-product reporting solution.

  • Own the end-to-end data architecture for a lakehouse/warehouse, streaming + batch pipelines, semantic layer, and Business Intelligence.
  • Define a canonical insurance data model spanning policy, rating, endorsements, claims, billing, receivables/payables, and broker accounting—plus conformed dimensions (party, product, coverage, risk unit, geography, time).
  • Establish robust data contracts and versioned schemas with product teams; drive event standards for policy lifecycle, claims, and accounting events.

Key Responsibilities:

  • Design multi-tenant data isolation and security, including workspace, schema, and row-level strategies; enforce Role-Based Access Control/Attribute-Based Access Control, encryption, and key management aligned to Service Organization Control 2, General Data Protection Regulation, and Payment Card Industry Data Security Standard.
  • Build the ingestion and transformation layer: streaming (Kafka/Event Hubs) and batch (Extract, Load, Transform/Extract, Transform, Load) into a bronze/silver/gold (medallion) model; manage Slowly Changing Dimension, late-arriving data, and idempotency.
  • Stand up the semantic layer (e.g., Power BI/Fabric/Looker semantic models) with governed, reusable metrics.
  • Institute data quality and observability: checks, SLAs/SLOs, lineage, and monitoring (contracts, schema drift, nullability, referential integrity, reconciliation to source).
  • Own governance & compliance: metadata, lineage, catalog, Personal Identifiable Information handling, retention, audit trails; champion Purview (or equivalent) and data stewardship processes.
  • Drive performance, reliability & cost: partitioning/clustering, query acceleration, workload management, caching, workload isolation, and cost guardrails.
  • Publish the tooling roadmap: Azure-native and complementary tools (Azure Data Lake Storage Gen2/Fabric or Databricks + Delta, Synapse/Fabric pipelines, Azure SQL/PostgreSQL, Purview, Key Vault, Power BI).
  • Enablement: reference implementations, style guides, model playbooks; run data design reviews with product squads; mentor data engineers/analysts.
  • Release management for data: Continuous Integration/Continuous Deployment for pipelines/models, automated tests (unit/data tests), backward-compatible schema versioning, and environment promotions.
  • Collaborate with Product, Engineering, and Implementation to prioritize analytics use cases and deliver roadmaps tied to customer outcomes.

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