What You'll Do- Design, develop, and maintain enterprise ETL pipelines using Azure Data Factory (ADF), Informatica PowerCenter, and Python-based frameworks.
- Build and optimize scalable data processing solutions using Python, Spark, and Databricks.
- Write and optimize SQL and stored procedures across relational platforms such as Snowflake, Oracle, and SQL Server.
- Follow data engineering best practices for performance, reliability, reusability, and security.
- Support Medicaid analytics and federal reporting initiatives (e.g., T-MSIS, PERM, MARS, Quality of Care).
- Develop robust data validation, reconciliation, and audit-traceable data pipelines.
- Collaborate with analysts, QA, and reporting teams to ensure data quality, accuracy, and timeliness.
- Participate in cloud migration and modernization initiatives within Azure-based architectures.
- Support production operations, incident resolution, and root cause analysis.
Participate in code reviews, source control, and CI/CD processes using Azure DevOps and GitHub.
Requirements
- 5+ years of data engineering experience with a focus on enterprise data warehousing.
- 5+ years of hands-on ETL development using Informatica PowerCenter, Teradata, Azure Data Factory, or similar tools.
- 5+ years of Python development for data engineering and automation.
- 5+ years of Teradata experience, including Teradata loader utilities.
- 3+ years of experience with Spark-based processing frameworks (Databricks or equivalent).
- Solid SQL expertise and experience with relational databases (such as Snowflake, Oracle, SQL Server).
- 3+ years of experience with Snowflake using SnowSQL and Snowpark (Python).
- Experience with source control and DevOps practices (Azure DevOps, GitHub, CI/CD).
- Proven solid analytical, problem-solving, and troubleshooting skills.
- Periodic travel may be required based on project or customer needs.
Preferred Qualifications- Bachelor's degree or higher in Computer Science, Engineering, Analytics, or a related field.
- Azure certifications related to data engineering or analytics.
- Experience supporting State Medicaid EDW or MMIS analytics environments.
- Healthcare or public sector analytics experience (Medicaid / Medicare preferred).
- Data modeling experience in enterprise data warehouse environments.
- Scripting experience (PowerShell, Bash) for automation and orchestration.
- Experience designing or consuming APIs (REST) within data platforms.
- Familiarity with data quality frameworks, reconciliation, and audit support.
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