Senior Data Engineer

The Washington Metropolitan Area Transit Authority is seeking a Senior Data Engineer in Alexandria, VA (onsite) to help strengthen asset reliability through telematics-driven insights. In this role, you will lead the development and maintenance of data pipelines, monitoring systems, predictive maintenance strategies, and reporting capabilities that support data-driven reliability-centered maintenance and help prevent unplanned downtime.

What you’ll do

• Build and maintain data workflows using ETL (extract, transform, load) from telematic systems with Microsoft Fabric Data Factory and Python.
• Develop condition monitoring capabilities by organizing and deploying systems that monitor real-time and historical condition and telematics data.
• Keep dataflows running reliably by diagnosing and resolving workflow issues, addressing data performance concerns, and ensuring data availability.
• Deliver business intelligence through AI-assisted data transformations, semantic models, and Power BI reports to surface early signs of component degradation or failure.
• Manage large-scale relational databases that support ETL processes while maintaining data quality and integrity.
• Integrate telematics with CMMS to enable automated alerts and the creation of maintenance repair records.
• Refine predictive maintenance approaches, including developing and adjusting predictive maintenance strategies and thresholds.
• Analyze asset health and failure indicators using equipment health signals such as vibration, temperature, pressure, and fault codes to detect abnormal trends.
• Track program performance by developing and monitoring KPIs related to asset health and condition monitoring program compliance.
• Support continuous improvement to enhance equipment reliability and asset lifecycle performance.
• Maintain documentation including reports and dashboards for system health and performance.
• Evaluate data against reliability models by assessing telematics data against established thresholds, failure modes, and reliability models, and performing root cause analysis (RCA) on failures and near-misses.
• Collaborate across teams with reliability engineers, asset engineers, maintenance teams, and IT to support continuous integration and smooth operations of condition monitoring processes.
• Train peers and end users on tools developed for asset health and performance monitoring.
• Research and provide feedback on condition monitoring technologies and predictive maintenance tools, including opportunities to incorporate them into existing equipment.
• Promote safety expectations by maintaining awareness and accountability with safety policies and procedures, reporting safety concerns consistent with the Agency Safety Plan, other regulatory requirements within the Safety Management System, and just culture principles.

Required qualifications

• Knowledge of how telematic systems can be leveraged to improve reliability.
• Knowledge and understanding of at least one programming language (SQL, Informatica, or Python).
• Knowledge of using a Computerized Maintenance Management System (CMMS) to analyze, query, and collect maintenance history.
• Strong skills manipulating large data sets using tools including Microsoft Excel, Tableau, or Power BI.
• Communication and influencing skills, including conveying high level technical concepts with non-experts and business leaders.
• Reporting skills to develop and present findings, analysis, and recommendations to different audiences within the Authority.
• Initiative to improve internal processes and customer service delivery.
• Ability to translate business priorities into plans, delivery roadmaps, and measurable outcomes.
• Ability to prioritize work and manage multiple responsibilities.
• Ability to organize and summarize large data sets into key findings.
• Ability to be available 24 hours, 7 days a week.

Minimum experience and education

• Minimum experience: Seven (7) years of progressive experience in engineering, reliability, maintenance, data science, data analytics, and/or related technical fields, including at least 2 years of ETL experience.
• Minimum education: Bachelor’s degree in Computer Science, Reliability, Electrical, Mechanical, or related engineering field (including Data Science). In lieu of a bachelor’s degree, a High School Diploma or GED plus four (4) years of experience in an electrical, mechanical maintenance role or data analytics may be considered, in addition to the experience stated above.

Preferred qualifications

• Experience in a reliability engineer role.
• Experience with ETL/data pipeline modernization.
• Experience with Machine Learning.
• Proficiency in Python, R, SQL, or DAX.
• ASQ-CRE or CMRP certification.
• Experience with mechanical/engineering systems.

Tools and technologies

• Microsoft Fabric Data Factory, Python
• Microsoft Excel, Tableau, Power BI
• SQL, Informatica
• Maximo, Oracle Databases, SQL Developer
• Microsoft Office Suite, Microsoft Visual Studios
• Cognos BI, PowerPoint, Access, Word
• Data visualization software including MS Power BI and Cognos BI

Supervisory responsibility: Not responsible for supervising others.