Unified Data Architect

4 days ago

Noida, Uttar Pradesh, India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

We are seeking a seasoned professional to spearhead our data integration and architecture efforts.

This critical role will be responsible for designing and implementing pipelines that unify CRM, billing, support, and SaaS app data into our Azure-native data fabric.

The ideal candidate will have expertise in data engineering and platform architecture, with a passion for solving complex data puzzles.

  • Develop and maintain ingestion pipelines from various sources, including CRMs, billing systems, and support tools, ensuring seamless data flow into our Azure Fabric Bronze/Silver layers.
  • Curate standardized models in Fabric Silver → Gold using Canonical RevAi Schema (CRS), including SCD2 handling, PII tagging, and business-rule conformance.
  • Optimize low-latency egress pipelines from Fabric → Postgres (staging → ext_* → app consumption), guaranteeing subsecond query performance for AI agents.
  • Implement tenant isolation via RLS in Postgres and Purview policies in Fabric, ensuring strict multi-tenancy and compliance with residency rules.
  • Ensure observability & SLAs: freshness checks, rowcount anomaly detection, and DQ tests across Bronze/Silver/Gold.
  • Contribute to FinOps dashboards by instrumenting pipeline cost metrics, cache hit rates, and egress efficiency.
  • Collaborate with AI engineers to ensure pgvector embeddings and agent run data integrate seamlessly into the operational data store.
  • Develop runbooks for DR/retention/erasure, and actively participate in quarterly pen-test preparations.

Required Skills:

  • At least 2–4 years of experience in data engineering / integration roles.
  • Hands-on experience with Azure Data Factory, Azure Fabric (OneLake/Lakehouse), or equivalent (Databricks/Snowflake acceptable).
  • Strong SQL and PostgreSQL experience (MERGE, staging, RLS, partitioning).
  • Experience with CDC, batch ingestion, or event streaming (Airflow, dbt, Kafka, or Fabric pipelines).
  • Comfort with data governance concepts (Purview, PII tagging, masked views, data lineage).

Nice-to-Have Skills:

  • Familiarity with pgvector, embeddings, or AI data models.
  • Prior exposure to multi-tenant SaaS architectures.
  • Experience with observability tooling (freshness checks, data quality gates, anomaly detection).
  • Familiarity with FinOps or cost-optimization in data pipelines.
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