Data Bricks Architect

Roles and Responsibilities :

1.Design end-to-end Databricks Lakehouse architectures spanning ingestion, transformation, governance, ML, and consumption layers — aligned to Medallion Architecture principles.

2.Drive EDW modernization engagements, including migration strategies from legacy platforms (Teradata, Netezza, Oracle, SAS, Greenplum, Synapse, Snowflake,
on-prem Hadoop) to Databricks, with clear wave planning, risk mitigation, and TCO/ROI articulation.

3.Advise customers on the adoption of advanced Databricks features.

4.Lake flow Declarative Pipelines (LDP / formerly DLT) for production-grade ETL with built-in data quality and lineage.

6.Lake flow Connect for managed ingestion from SaaS, databases, and file sources.
7.Serverless Compute (SQL warehouses, jobs, notebooks) for cost and operational efficiency.
8.Unity Catalog for unified governance, lineage, and fine-grained access control.
9.Databricks Asset Bundles (DAB) for CI/CD and environment promotion
10.Databricks SQL, AI/BI Dashboards, Genie for self-service analytics
11.Expertise in Data Bulid Tool (DBT) and Databricks Autoloader
12.Databricks SQL, AI/BI Dashboards, Genie for self-service analytics
13.MLflow, Model Serving, and Mosaic AI for ML and GenAI workloads
14.Conduct architecture deep-dives, PoCs, and workshops — including cost modelling roadmaps, runbooks and executive presentations.
15.Produce Client ready deliverables. HLD / LLD documents, reference architecture, migration road maps, runbook and execution presentations
16.Partner with sales, delivery, and Databricks field teams to shape proposals, SoWs, and bid
responses.
17.Stay ahead of the Databricks product roadmap and evangelize new capabilities internally
and with customers.
18.Mentor data engineers, platform engineers, and junior architects on Databricks best

Job Requirements :

Databricks certifications: Certified Data Engineer Professional, Certified Machine Learning Professional, or Databricks Certified Solutions Architect Professional.
•Experience with DR architectures (Delta Deep Clone, cross-region replication, RPO/RTO design).
•Exposure to MLOps / GenAI patterns on Databricks (MLflow, Model Serving, Vector Search, Mosaic AI Agent Framework)
•Familiarity with legacy ETL/ELT platforms (Informatica, ODI, SAS DI, DataStage, Talend) for migration credibility.
•Experience with Terraform / Databricks Asset Bundles for IaC and CI/CD.
•Working knowledge of Immuta, Collibra, Purview, or Alation for governance integration.
•Industry depth in BFSI, Insurance, Retail, Manufacturing, or Healthcare.