Senior ETL / Python Developer Job at Datamaxis in Springfield
Datamaxis, Springfield, IL, United States
Our client is seeking a hands‑on Senior Data Engineer (ETL / Python Developer) to support the Enterprise Data Warehouse (EDW) and Analytics Program. This role plays a critical part in designing, developing, and maintaining scalable data ingestion and transformation pipelines that support Medicaid analytics, federal reporting, and enterprise decision support.
The ideal candidate brings strong ETL and Python engineering expertise, experience working with large healthcare datasets, and the ability to operate effectively in a regulated, audit‑sensitive environment. This is a delivery‑focused role requiring close collaboration with architects, analysts, QA, PMs, SMEs, developers, and reporting BI teams across both legacy and cloud‑based platforms.
Primary Responsibilities
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
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
Write and optimize SQL and stored procedures across relational platforms such as Snowflake, Oracle, and SQL Server
Participate in cloud migration and modernization initiatives within Azure‑based architectures
Collaborate with analysts, QA, and reporting teams to ensure data quality, accuracy, and timeliness
Follow data engineering best practices for performance, reliability, reusability, and security
Support production operations, incident resolution, and root‑cause analysis
Participate in code reviews, source control, and CI/CD processes using Azure DevOps and GitHub
Required Qualifications
5+ years of data engineering experience with a focus on enterprise data warehousing
5+ years of hands‑on ETL development using Informatica PowerCenter, Azure Data Factory, or similar tools
5+ years of Python development for data engineering and automation
3+ years of experience with Spark‑based processing frameworks (Databricks or equivalent)
Strong SQL expertise and experience with relational databases (such as Teradata, Snowflake, Oracle, SQL Server)
Experience with source control and DevOps practices (Azure DevOps, GitHub, CI/CD)
Bachelor’s degree or higher in Computer Science, Engineering, Analytics, or a related field
Strong analytical, problem‑solving, and troubleshooting skills
Preferred Qualification
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
Azure certifications related to data engineering or analytics
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The ideal candidate brings strong ETL and Python engineering expertise, experience working with large healthcare datasets, and the ability to operate effectively in a regulated, audit‑sensitive environment. This is a delivery‑focused role requiring close collaboration with architects, analysts, QA, PMs, SMEs, developers, and reporting BI teams across both legacy and cloud‑based platforms.
Primary Responsibilities
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
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
Write and optimize SQL and stored procedures across relational platforms such as Snowflake, Oracle, and SQL Server
Participate in cloud migration and modernization initiatives within Azure‑based architectures
Collaborate with analysts, QA, and reporting teams to ensure data quality, accuracy, and timeliness
Follow data engineering best practices for performance, reliability, reusability, and security
Support production operations, incident resolution, and root‑cause analysis
Participate in code reviews, source control, and CI/CD processes using Azure DevOps and GitHub
Required Qualifications
5+ years of data engineering experience with a focus on enterprise data warehousing
5+ years of hands‑on ETL development using Informatica PowerCenter, Azure Data Factory, or similar tools
5+ years of Python development for data engineering and automation
3+ years of experience with Spark‑based processing frameworks (Databricks or equivalent)
Strong SQL expertise and experience with relational databases (such as Teradata, Snowflake, Oracle, SQL Server)
Experience with source control and DevOps practices (Azure DevOps, GitHub, CI/CD)
Bachelor’s degree or higher in Computer Science, Engineering, Analytics, or a related field
Strong analytical, problem‑solving, and troubleshooting skills
Preferred Qualification
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
Azure certifications related to data engineering or analytics
#J-18808-Ljbffr