Senior Data Manager - ETL, SQL & Analytics

SMX; Huntsville (TN); On-site; USD 65,000 - 80,000; Full time

Benefits offered by this job

Health insurance

Paid leave

Retirement plan

Job summary

SMX seeks a Data Manager to support a government client in Huntsville, AL, leveraging data governance and hands-on scripting to automate complex data operations.

The role spans data management, integration, and analytics, including data collection, validation, storage, dissemination, and archival, with ETL automation using Python and SQL for data profiling to ensure high-quality data for BI/AI initiatives.

Qualifications

• Secret clearance required and 3+ years of experience.
• Bachelor's degree in data management, information systems, engineering, or related field; or high school diploma with 7 years of experience.
• Ability to multi-task and work across different projects.
• Strong communication skills and ability to work independently or in a team.

Responsibilities

• Collaborate with team and customers to manage program data across MDA system.
• Manage full lifecycle of data events: collection, validation, storage, dissemination, archival.
• Support data integration and interoperability across programs with authoritative data sources.
• Design, write, test, and maintain Python scripts to automate ETL and archiving.
• Write SQL queries to profile data and analyze discrepancies; optimize data schemas.
• Support mission execution via pre-test validation of data systems and data flows.
• Conduct data analysis to identify gaps and areas for improvement.
• Prepare data for business intelligence, AI/ML and advanced analytics.

Skills

Clearance: Secret

Multitasking

Communication skills

Team collaboration

Education

Bachelor's degree in a related technical field

High school diploma with 7 years experience

Tools

Python

SQL

ETL

APIs

CI/CD

Job description

SMX seeks a Data Manager to support a government client in Huntsville, AL, leveraging data governance and hands-on scripting to automate complex data operations.

The role spans data management, integration, and analytics, including data collection, validation, storage, dissemination, and archival, with ETL automation using Python and SQL for data profiling to ensure high-quality data for BI/AI initiatives.