Ab Initio Developer
Location: Jacksonville, FL
Duration: Long term
A Senior Ab Initio developer with:
- 5+ years of hands-on Ab Initio development in enterprise environments (preferably healthcare or regulated industries).
- Proven ability to:
- Design and debug complex Ab Initio graphs (multi-file, multi-database workflows).
- Write data quality rules and scripts to clean/validate healthcare datasets.
- Collaborate with cross-functional teams (DBAs, analysts, vendors) to align ETL pipelines with analytics needs.
This position centers on ETL/ELT development, data quality, and governance using Ab Initio to support large-scale data pipelines for analytics. The role emphasizes:
- Building and Optimizing ETL Workflows :
- Designing and coding Ab Initio graphs (workflows) for data integration, transformation, and batch processing.
- Collaborating with teams to ensure data pipelines meet data quality standards and business rules.
- Data Quality & Governance :
- Profiling data, identifying issues (e.g., duplicates, inconsistencies), and implementing fixes.
- Enforcing data governance protocols to ensure compliance (e.g., HIPAA, PHI for healthcare data).
- Integration with Modern Tools :
- Working with relational databases (e.g., Netezza, SQL Server), NoSQL databases , and APIs (RESTful services, JSON).
- Optional: Cloud platforms (AWS, Azure) and hybrid architectures.
- Ab Initio Expertise :
- Hands-on experience with Ab Initio Co> Operating System , Graph Development , and Data Quality tools (e.g., DQ Analyzer, DQ Rules).
- Ability to design workflows for large-volume batch processing (e.g., claims, member data).
- SQL & Scripting :
- Advanced SQL for ELT (Extract-Load-Transform) and query optimization.
- Unix/Linux shell scripting for job automation, error handling, and file management.
- ETL Tool Familiarity :
- Experience with tools like Informatica , Talend , or MuleSoft is a plus (for cross-tool collaboration or migration projects).
- Data Warehousing :
- Understanding of data warehousing concepts (star schema, slowly changing dimensions) and integration with data marts .
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