Job Description
Senior Data Engineer | Richmond, VA (Hybrid) 26-00558
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- 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
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We are seeking 2 experienced Senior Data Engineers to join an enterprise technology team supporting large-scale data engineering initiatives.
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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.
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Schedule: Alternating weeks onsite and remote (5 days in office, followed by 5 days remote)
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Experience: 5–7+ years of Data Engineering experience
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Education: Bachelor's degree or higher in Computer Science, Information Systems, Mathematics, or a related discipline
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Occasional after-hours or weekend support may be required.
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What You'll Be Doing
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- 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.
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Required Technical Skills
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- 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.
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Nice to Have
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- 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.
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Ideal Candidate
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We are especially interested in candidates with experience in:
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- Large-scale commercial utilities organizations.
- Enterprise data engineering environments.
- Large-scale capital projects.
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We are looking for professionals who demonstrate strong ownership, collaboration, communication, adaptability, independent problem-solving, and a commitment to delivering high-quality solutions.
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Interview Process
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- First-round interview via Microsoft Teams (camera on).
- Candidates who perform well will advance to a technical interview.
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Interested or know someone who would be a great fit?
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Please send your updated resume via LinkedIn message or reach out directly to discuss this opportunity.
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