Data Architect

Greeting From Lightning Minds,

Please find the job description below.

Location : Remote

Duration : 12 Months

Role Summary
Senior architecture role focused on modern healthcare data platforms, Medicaid/T-MSIS domain expertise, and
large-scale modernization using AWS Databricks.
Roles & Responsibilities
 Define scalable data architecture patterns using AWS Databricks, PySpark, Spark SQL, Delta Lake, and
lakehouse / medallion architecture principles.
 Design canonical/conformed data models, metadata-driven transformation patterns, reusable rule frameworks,
and governed reference-data structures.
 Translate T-MSIS and Medicaid business requirements into technical architecture and data-model decisions.
 Guide modernization of legacy ETL and batch solutions into cloud-native Databricks implementations.
 Provide architectural guidance for source-to-target mapping, state-specific rules, validation, reconciliation,
lineage, audit, and data governance.
 Review technical designs, data models, transformation logic, and engineering standards.
 Work closely with business SMEs, mapping analysts, data engineers, QA, and platform teams to resolve
complex data and domain issues.
 Mentor engineering teams and provide technical leadership on performance, scalability, maintainability, and
security.
Required Skills & Experience
 10+ years of data engineering / architecture experience, including 3+ years in a senior or lead architect role.
 Strong hands-on experience with AWS Databricks, PySpark, Spark SQL, Delta Lake, Databricks Workflows,
and lakehouse / medallion architectures.
 Strong understanding of AWS data-platform services and integration patterns, including S3, IAM,
networking/security concepts, and cloud data movement.
 Strong data modeling experience covering raw, conformed, curated, and regulatory-reporting data layers.
 Experience designing metadata-driven / configuration-driven transformation and business-rules frameworks.
 Experience with Unity Catalog, data lineage, access controls, auditability, and governed reference data.
 Strong SQL and experience with Oracle, SQL Server, DB2, flat files, and enterprise source systems.
 Experience modernizing legacy ETL platforms such as DataStage, SSIS, Informatica, C/Linux, COBOL, or
custom batch frameworks.
 Experience with Git, CI/CD, code review, automated testing, and deployment practices for Databricks.
 Strong communication skills and ability to convert complex business and regulatory requirements into practical
architecture.