Systems Engineer

Position Summary

The Senior Data Analyst / Data Computer Systems Engineer will provide expert-level data development and data systems engineering services for the National Park Service enterprise data management systems. This position is responsible for developing and maintaining complex data processing software, managing data pipelines, and leading data migration activities across both alphanumeric and geospatial data systems. The role requires advanced technical expertise in SQL, Python programming, and enterprise-level spatial data management to support mission-critical data infrastructure and business requirements.

Duties May Include :

Design and develop complex data models, database schemas, and data pipelines for enterprise systems

Lead data migration planning and implementation from legacy to modern data structures

Write advanced SQL, T-SQL, and PL / pgSQL procedural code for Microsoft SQL Server and PostgreSQL databases

Architect and implement enterprise-level spatial data management solutions within RDBMS and geodatabases

Build advanced coding and infrastructure for optimal ETL processes using Cloud and SQL technologies

Conduct complex data quality analysis and implement comprehensive business and quality rules

Design and implement quality management processes for large-scale data migration activities

Lead efforts in re-designing infrastructure for greater scalability and optimizing data delivery

Automate manual processes and implement internal process improvements

Provide technical leadership for data-related issues and infrastructure needs

Collaborate with stakeholders to identify process improvement opportunities and propose system modifications

Structure and optimize both small and large data sets for efficient retrieval and analysis

Define and maintain complex domain definition requirements and permissible values

Lead development of comprehensive metadata records for data management systems and standards

Mentor junior team members and provide technical guidance on complex data engineering challenges

Requirements

Required Qualifications :

Bachelor's degree in Computer Science, Data Science, Engineering, or related technical field

Minimum 5 years of experience in data analysis and engineering activities including data schema development

Expert-level proficiency in SQL, Python programming, and database procedural languages

Extensive experience with data migration activities and ETL / ELT processes

Advanced knowledge of Microsoft SQL Server and PostgreSQL database systems

Strong experience with enterprise spatial data management and geodatabases

Proven ability to design and implement scalable data architectures

Experience with cloud platforms (Microsoft Azure or AWS) for data processing

Active NAC or NACI security clearance eligibility

Desired Qualifications :

Advanced degree in Computer Science, Data Engineering, or related field

Certification in cloud platforms (Azure Data Engineer, AWS Data Analytics)

Experience with ESRI Enterprise Geodatabases and ArcGIS platforms

Knowledge of modern data stack technologies and data lake architectures

Experience with Azure DevOps Server and Github for code management

Understanding of data governance and metadata management principles

Experience with API development and microservices architectures

Knowledge of machine learning and advanced analytics techniques

Benefits

At Trinity Global Consulting (TGC), we value our employees and provide a comprehensive benefits package that includes :

• Medical, Dental & Vision Coverage – Full coverage for employees and family through CareFirst and VSP.
• Paid Time Off – Minimum of 2 weeks PTO in accordance with contract requirements.
• Paid Holidays – 11 federal holidays observed annually.
• Disability & Life Insurance – Short-term / long-term disability, life insurance, and AD&D coverage included.
• 401(k) Retirement Plan – Competitive plan managed through Ameritas .
• Professional Training – Formal training provided as required, with additional learning opportunities based on role.