Data Architect

Role :Data Architect (Senior / Principal) — Platform Data & Analytics

Location-Pune-Hybrid

Experience: - 12+

Job Description:

We are looking for a senior data architect to own the operational data model on SQL server and the data warehouse and analytics layer. The role spans two foundational pillars of our data layer and requires horizontal influence across every product team.

What You'll Do

1. Own the operational data model on SQL server -schema, partitioning, tenant isolation, indexing strategy, locking and concurrency design. Solve the scaling problems before they hit customers.

2. Own the data warehouse and analytics layer — dimensional model, semantic layer, ETL/ELT, warehouse modernization on the AWS data stack.

3. Stay deeply hands-on with SQL, modeling, and pipeline code — Write reference pipelines, complex stored procedures, dimensional models, and the first cut of every new data capability.

4. Govern the data layer for multi-tenant SaaS — partitioning, tenant isolation, row-level security, tenant onboarding/offboarding, data residency

5. Set data standards across product teams — schemas, contracts, naming, change management, lineage, ownership, deprecation.

6. Build the Bi and analytics platform

7. partner with the Ai team on data for Ai

8. Own data quality, lineage, and governance

9. Lead architecture reviews and design partnerships

10. Multiply senior data talent

11. Own the hardest production data problems

12. Drive build vs. buy vs. partner decisions

What We're Looking For

1. 12+ years in data engineering / data architecture
2. Has solved real SQL Server scaling problems at production scale — this is the bar.
3. Deep, current SQL Server craft — T-SQL, query plans, statistics, indexing strategy.
4. Proven multi-tenant data architecture for enterprise SaaS
5. Strong data warehouse architecture — built warehouses, not just reported off them. — Kimball / Inmon
6. Deep BI experience
7. Production experience with event-driven and streaming data — CDC (Debezium / DMS), Kafka / MSK / Kinesis
8. Excellent written communication — RFCs, data contracts, schema docs, ADRs. Can hold a room of senior engineers and a room of execs in the same week.

Pragmatic judgment — bias toward the simplest model that scales, willingness to refactor schemas, instinct for when to denormalize vs. star vs. snowflake schema, and when to push work to the warehouse vs. keep it operational.

Nice to Have :

1. US healthcare, behavioral health, claims, credentialing, or EHR data familiarity

2. HIPAA / PHI handling, PHI segregation, audit and lineage for regulated data

3.Warehouse modernization on AWS — Redshift RA3 / serverless, Glue, Athena Federated Query, dbtRedshift

1. AI / ML data experience
2. Data catalog and quality tooling — Purview, Collibra, Open Metadata, Great Expectations, dbt tests
3. Modernization track record — on-Prem warehouse → cloud, monolithic reporting → semantic modeling, legacy
4. SSRS → modern BI
5. Open-source contributions, technical writing, conference talks, or patents