A bachelor's degree in computer science (Required)
15 years of experience in a complex computing environment may be considered in lieu of degree.
7 years of experience in information technology (Required)
4 years or more of experience in project management (Required)
8+ years in data engineering with strong experience in modern data platforms (Azure preferred)
Hands-on expertise in Databricks and PySparkfor large-scale data processing
Strong understanding of medallion architecture (Bronze / Silver / Gold)
Experience designing metadata-driven or configuration-driven data pipelines
Deep knowledge of data ingestion patterns (batch, file-based, incremental loads)
Strong experience with data modeling concepts (keys, SCD, merge strategies)
Experience implementing data quality frameworks and validation rules
Proficiency in SQL and distributed data processing concepts
Experience with Azure Data Lake Storage (ADLS) and file-based ingestion patterns
Familiarity with CI/CD, Git, and deployment practices in data engineering
Experience with data catalog and governance tools (DataHub, Collibra, Alation, etc.)
Exposure to customer 360 / MDM / CRM data integration (Salesforce, Dynamics, etc.)
Experienceworking in healthcare or regulated environments (HIPAA, PHI handling)
Familiarity withUnity Catalog and data access governance models
Experience integrating dataplatforms with workflow tools like ServiceNow for access management
Exposure to event-driven ingestion patterns(file triggers, streaming, etc.)
Experience working in large-scale migration or modernization programs
Strong stakeholder management experience working with business, architecture, and vendor teams
Experience working in large-scale enterprise data platforms
Experience enabling self-service data access and governance
Familiarity with API-driven data integration patterns