Senior Data Engineer

Senior Data Engineer | Richmond, VA (Hybrid)26-00558

• Onsite; candidates must be local or able to commute to Richmond, VA
• Must be eligible for direct W-2 employment, with no C2C, subcontracting, or H-1B sponsorship

We are seeking 2 experienced Senior Data Engineers to join an enterprise technology team supporting large-scale data engineering initiatives.

This is an exciting opportunity for hands-on data engineering professionals who enjoy building complex data pipelines, optimizing enterprise data platforms, and driving innovative data solutions.

Schedule: Alternating weeks onsite and remote (5 days in office, followed by 5 days remote)

Experience: 5–7+ years of Data Engineering experience

Education: Bachelor's degree or higher in Computer Science, Information Systems, Mathematics, or a related discipline

Occasional after-hours or weekend support may be required.

What You'll Be Doing

• Design, develop, and optimize enterprise-scale data pipelines and ETL/ELT solutions.
• Build high-volume, scalable batch and real-time data processing workflows.
• Lead SQL development, performance tuning, and data warehouse optimization.
• Develop and support complex data transformations and dimensional data models.
• Implement reliable, production-ready pipelines with monitoring, error handling, and recovery capabilities.
• Work with architecture, infrastructure, application, governance, and DataOps teams.
• Drive data quality, security, observability, and performance best practices.
• Troubleshoot production issues and lead root cause analysis.
• Support analytics, reporting, and AI/ML data initiatives.

Required Technical Skills

• Advanced SQL, ELT development, and performance tuning.
• Strong experience with Oracle Exadata, Snowflake, or comparable enterprise data warehouses.
• Hands-on experience with ETL/ELT platforms such as Talend, dbt, or Informatica.
• Strong understanding of data warehousing architecture and dimensional modeling.
• Experience designing and supporting large-scale production data pipelines.
• Python and Shell scripting.
• Data virtualization technologies such as Denodo, Composite, Dremio, or Starburst.
• DataOps practices, CI/CD, and observability.
• Experience supporting enterprise ETL development and production processes.

Nice to Have

• Experience supporting AI/ML and advanced analytics pipelines.
• AWS, Azure, or GCP cloud experience.
• Experience with Apache Kafka, Kafka Connect, Spark Streaming, Apache Flink, or Cribl.
• Real-time streaming and event-driven data architecture experience.
• Experience with enterprise data standards and reference architecture.
• Cloud data warehouse cost and performance optimization.

Ideal Candidate

We are especially interested in candidates with experience in:

• Large-scale commercial utilities organizations.
• Enterprise data engineering environments.
• Large-scale capital projects.

We are looking for professionals who demonstrate strong ownership, collaboration, communication, adaptability, independent problem-solving, and a commitment to delivering high-quality solutions.

Interview Process

• First-round interview via Microsoft Teams (camera on).
• Candidates who perform well will advance to a technical interview.

Interested or know someone who would be a great fit?

Please send your updated resume via LinkedIn message or reach out directly to discuss this opportunity.

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