Staff Data Engineer building pipelines, models, and infrastructure for exacare ai’s post - acute care AI platform. Turning healthcare data into reliable foundations for product, analytics, and ML workflows.
About the role
- Data Engineer at The Fedcap Group architecting and leading enterprise data warehouse solutions. Focused on enabling scalable growth and operational excellence across the organization.
Responsibilities
- Deliver Reliable, Analytics-Ready Data Models
- Build Secure and Compliant Data Infrastructure
- Lead development of dbt and transformation workflows
- Ensure performance and cost optimization
- Enable end to end Data pipeline
- Directly Support Business & Analytics Teams
- Collaborate with the Head of Data and Analytics to implement the enterprise Medallion Architecture (Bronze → Silver → Gold)
- Design, build, and maintain data ingestion pipelines in Azure Data Factory (ADF)
- Configure and manage secure integrations between Azure and Snowflake
- Develop and optimize Snowflake data models
- Implement role-based access control (RBAC), data masking, and row/column-level security in Snowflake
- Build and maintain a modular dbt framework
- Create and manage CI/CD pipelines for dbt using GitHub Actions or Azure DevOps
- Write and optimize complex SQL and Python scripts
- Implement data validation, quality checks, and monitoring frameworks
- Collaborate directly with BI, Analytics, and Data Science teams
- Take end-to-end ownership of assigned data engineering projects: requirements - design - build - deploy - support
- Document pipelines, transformations, and models to ensure reproducibility and team-wide adoption
Requirements
- Bachelor’s degree in information systems, Computer Science, Engineering, or related field.
- Advanced degrees in related fields are plus, however hands-on experience is strongly preferred.
- Snowflake Snowpro Advanced Data Engineer / Architect certification (Preferred).
- 5+ years of proven experience in data engineer roles.
- Deep expertise in enterprise system implementations, data lifecycle management, modular framework and data platform architecture.
- Strong hands-on experience with dbt, Azure and Snowflake are a must.
- Demonstrated ability to design and implement scalable, secure and modular data pipeline.
- Experience with data quality frameworks, lineage and governance practice.
- Track record of delivering end-to-end data solutions in cloud environments.
Benefits
- Professional development opportunities • Flexible work arrangements
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