Remote -AWS Databricks Architect with .net

Role: Information Management / Databricks Architect

Location: Remote 

Duration: 12+ Months

Operational Data Stack: SQL Server / T-SQL , COBOL Flat Files, Dapper / ORM, C# / .NET 8 ,ASP.NET Core APIs

Cloud & Analytics Platform: AWS (S3, Glue, Athena, RDS),Databricks / Apache Spark , Amazon Bedrock , Delta Lake ,AWS IAM / Lake Formation

Data Engineering & Governance: ETL / ELT Pipeline Design, Medallion Architecture , Data Catalog & Lineage, Data Governance Frameworks , BI / Semantic Layers

 Responsibilities:

•              Design and govern TAI''s enterprise data architecture — spanning the operational SQL Server core, cloud-native data stores on AWS, and modern analytics platforms including Databricks

•              Define the data platform strategy that supports TAI''s evolution from client-installed deployments to a centralized, multi-tenant SaaS model — including data isolation, partitioning, and residency patterns for regulated insurance data

•              Architect data ingestion pipelines that consolidate data from TAI''s diverse client environments (SQL Server, COBOL flat files, network-share repositories) into unified analytics-ready stores

•              Own data quality frameworks: define validation rules, lineage tracking, and observability tooling for all data pipelines

•              Expert knowledge of schema design, medallion architecture (Bronze/Silver/Gold), and data contract standards for central data lakes and analytical platform

•              Professional experience building AI data platforms — ensuring training datasets, feature stores, and inference pipelines are governed, reproducible, and audit-ready

•              Define and enforce data governance standards across TAI''s platform — including data classification, PII handling, retention policies, and access controls appropriate for insurance-regulated environments

•              Ensure data architecture designs comply with state insurance regulatory requirements, SOC 2 controls, and client contractual obligations around data residency and sovereignty

•              Architect role-based data access patterns that support multi-client isolation: no client should be able to access or infer data belonging to another carrier

•              Own the data catalog and metadata management strategy — ensuring all data assets are discoverable, documented, and trusted

•              Partner with the TAI Architecture and Engineering to ensure data architecture aligns with platform architecture — no silos between operational systems and analytics

•              Mentor engineers in data engineering best practices: pipeline design, SQL optimization, dimensional modeling.

•              Engage with client-facing teams to understand reporting and data export requirements across TAI''s client base, translating them into scalable platform features

Thanks

Yashasvi Hasija

Team Lead | Empower Professionals

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   | Phone:  x 368 | Fax:

LinkedIn: linkedin.com/in/yashasvi-hasija-6a745625b

100 Franklin Square Drive – Suite 104 | Somerset, NJ 08873

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