Enterprise Data Integration Engineer (Python​/ETL) - Senior

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Full Time RMT-Hybrid, US

Salary Range: $90,000.00 To $ Annually

Enterprise Data Integration Engineer (Python/ETL) - Senior

Location: On-location at Pentagon (Hybrid and Remote eligible)

Level :
Senior

Clearance: Must be eligible for federal SECRET clearance

* Candidates must have the above clearance level and, at a minimum, be able to maintain this clearance during their employment with Montcure.

Montcure, LLC is a Service-Disabled Veteran-Owned Small Business (SDVOSB) founded with a vision to revolutionize consulting and advisory services through innovative, data-driven solutions. The Montcure team recognizes the unique challenges faced by organizations and governments in today’s rapidly evolving business environment.

Job Summary

Montcure is seeking an Enterprise Data Integration Engineer (Python/ETL) – Senior to support enterprise financial data integration and modernization efforts. This role focuses on designing, developing, and maintaining robust ETL/ELT data pipelines that transform complex data from multiple enterprise systems into trusted, business-ready datasets for downstream reporting, analytics, and business applications. The successful candidate will work closely with functional stakeholders to understand business rules, translate inconsistent source data into standardized data models, and implement scalable transformation logic using Python, SQL, and modern data engineering practices.

Key Responsibilities:

• Design, develop, test, and maintain scalable ETL/ELT data pipelines using Python, SQL, and modern data engineering practices.
• Maintain and enhance existing data pipelines as enterprise data sources, business rules, and reporting requirements evolve over time.
• Develop transformation logic that standardizes and integrates data from multiple enterprise source systems.
• Build reusable data processing components that support enterprise reporting and analytics.
• Monitor and adapt pipeline logic to accommodate changes in source systems, data structures, and evolving business requirements while preserving data quality and integrity.
• Optimize pipeline performance, reliability, scalability, and maintainability.

Data Integration & Transformation

• Analyze data from multiple enterprise systems and develop transformation logic that standardizes differing data structures, terminology, and business rules into consistent, business-ready datasets.
• Collaborate with functional subject matter experts to understand financial business rules, validate data interpretations, and ensure transformation logic accurately reflects business intent.
• Identify and resolve data quality, reconciliation, and normalization issues to ensure accurate, trusted, and traceable enterprise datasets.

Data Modeling & Governance

• Develop and maintain canonical datasets suitable for enterprise reporting and analytics.
• Support the ongoing evolution of canonical data models as new source systems, business entities, and reporting requirements are introduced.
• Maintain data lineage and traceability throughout the transformation process.
• Document transformation logic, mapping specifications, and business rules.
• Support data validation, reconciliation, and quality assurance activities.

Technical Collaboration

• Partner with application engineers, data modelers, and functional stakeholders to deliver trusted, production-ready data assets supporting enterprise reporting and business applications.
• Collaborate with downstream development teams to ensure datasets support evolving reporting, analytics, and application requirements.
• Participate in solution design, testing, troubleshooting, deployment, and continuous improvement activities.
• Provide technical recommendations that improve data quality, pipeline reliability, maintainability, and long-term scalability.

Required Qualifications:

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, Mathematics, or related field (or equivalent experience).
• 5+ years of experience developing enterprise ETL/ELT or data integration solutions.
• Strong Python programming skills for data processing and automation.
• Strong SQL skills, including complex joins, aggregations, and query optimization.
• Experience integrating data from multiple enterprise systems.
• Experience with data profiling, cleansing, normalization, reconciliation, and transformation.
• Experience creating source-to-target mapping documentation.
• Understanding of data lineage, metadata management, and data governance principles.
• Strong analytical, troubleshooting, and problem-solving skills.
• Strong written and verbal communication skills.

Preferred Qualifications:

• Experience working with Navy financial systems, financial data, or enterprise financial datasets (e.g., Navy ERP or other Department of the Navy financial applications).
• Experience supporting federal financial…