Geospatial Data Engineer Remote Jobs in Ohio (NOW HIRING)

Senior Data Engineer (Cloud & Data Modernization)

A-TEK is seeking a Senior Data Engineer to support enterprise data modernization, cloud-native data engineering, analytics enablement, and data governance initiatives for Federal customers. This role focuses on designing and implementing scalable data platforms, automated ETL/ELT pipelines, and modern cloud-based data solutions supporting scientific, operational, and mission-critical environments.

The ideal candidate combines strong hands-on engineering expertise with the ability to collaborate across technical and non-technical teams to modernize data ecosystems and improve enterprise data accessibility, quality, governance, and analytics capabilities.

NOAA experience is preferred. This position is remote and requires the ability to obtain and retain a public-trust clearance.

Responsibilities

• Design, develop, and optimize enterprise data warehouses and large-scale ETL/ELT pipelines
• Engineer cloud-native data processing solutions supporting structured, semi-structured, and unstructured data
• Develop scalable ingestion and transformation frameworks for high-volume and real-time data processing
• Support modernization of legacy data environments into cloud-based architectures
• Design and implement data models, schemas, and database structures optimized for analytics and reporting
• Develop metadata-driven automation, data quality validation, lineage tracking, and governance capabilities
• Build and maintain reporting, analytics, and dashboarding solutions supporting operational and executive decision-making
• Collaborate with architects, engineers, analysts, and business stakeholders to define technical requirements and implementation strategies
• Support AI/ML and advanced analytics initiatives through scalable data engineering and MLOps-ready infrastructure
• Implement Infrastructure-as-Code (IaC), CI/CD pipelines, and automated deployment processes
• Perform database tuning, query optimization, and performance engineering activities
• Support secure data management and compliance with Federal security and data governance requirements
• Provide technical leadership, mentoring, and engineering best practices across project teams

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field
• 7+ years of experience in data engineering, data warehousing, database engineering, or related disciplines
• Strong experience designing and implementing ETL/ELT pipelines and enterprise data warehouse solutions
• Experience with distributed processing frameworks and cloud-native data ecosystems
• Strong experience with data modeling, database design, and dimensional modeling techniques
• Experience implementing data governance, metadata management, data quality, and data integrity controls
• Proficiency with SQL and Python-based data engineering and automation
• Experience with cloud data platforms and services in AWS, Azure, or Google Cloud
• Experience supporting large-scale, modern data modernization initiatives
• Strong verbal and written communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
• Experience collaborating across cross-functional teams in Agile or DevSecOps environments

Preferred Qualifications

• NOAA or broader Federal civilian agency experience
• Experience supporting scientific, environmental, geospatial, or research data environments
• Experience with GIS or geospatial data platforms
• Experience with AI/ML data engineering or MLOps support
• Experience with Infrastructure-as-Code and CI/CD automation
• Familiarity with metadata management, data catalogs, and enterprise governance frameworks
• Experience with real-time streaming or event-driven data architectures
• AWS or Azure certifications

Preferred Technical Skills

• SQL Server, PostgreSQL, Oracle, or cloud-native databases
• Azure Data Factory, SSIS, Informatica, dbt, Airflow, or similar ETL frameworks
• Azure Synapse, Databricks, Spark, Hadoop, Kafka, or distributed analytics platforms
• Python, Pandas, NumPy, PySpark
• Power BI, Tableau, SSRS, or enterprise analytics platforms
• Docker, Kubernetes, Git, Azure DevOps, Jenkins, Terraform, or similar DevOps technologies
• REST APIs and data integration services

Compensation

• Salary Range: $160,000 - $170,000 annually (commensurate with experience, professional certifications and location)
• Benefits: Health, dental, and vision insurance; 401(k) with employer match; paid time off; professional development opportunities.