Data Engineer

Dominion Energy • Richmond, VA

1d • $81,900 - $106,400 • Hybrid

About The Position

Dominion Energy is committed to providing reliable, affordable, and increasingly clean energy that powers our customers every day. If you want to work for a purpose-driven company that values safety and collaboration, we’re looking for you. You won’t just find a job here; you’ll find your career. Review the position below and apply today. We offer a hybrid work schedule (one week in the office, one week of teleworking) to accommodate the need for flexibility.Military service members and veterans with ranks from E3-E5, W1-W2, or O1-O3, plus appropriate equivalent combination of education and years of experience as outlined below will be considered for this opportunity. At this time, Dominion Energy cannot transfer or sponsor a work visa or employment authorization for this position.This position does not offer relocation assistance. Job Summary
Data Engineer is responsible for designing, building, maintaining, and optimizing data solutions that collect, store, process, and make data accessible for analytics, reporting, and business decision-making. This role works closely with Data Product Owners, business stakeholders, analysts, and technical teams to develop scalable data pipelines, support data integration initiatives, and ensure the reliability, quality, and performance of enterprise data assets.
Under general supervision, designs, build and maintains medium complexity data pipeline/ETL processes ensuring that the code follows latest coding practices and industry standards.  Work closely with other developers and team members to understand the system end-to-end and perform system analysis.   Responsible for creating data pipelines, ensuring data quality, and optimizing data infrastructure. Complete the work needed to implement features from the product backlog.
Work closely with Product/Business Owner to understand stories and requirements from both Business and Technical perspective. Assist in building and maintaining scalable ETL/ELT pipelines. Support data ingestion from APIs, databases, and flat files. Clean, transform, and validate data to ensure accuracy and consistency. Write and optimize SQL queries for data extraction and reporting. 
Collaborate with data analysts and scientists to understand data needs. Monitor data workflows and troubleshoot pipeline issues. Document data processes and contribute to data engineering best practices. work closely with senior engineers, learning from their experience and expertise. Perform simple ad-hoc queries to answer specific business questions.

Requirements

• 2+ years of relevant experience.
• Understanding of Relational Database Management Systems (RDBMS).
• Knowledge of data warehousing concepts, including star and snowflake schemas.
• Familiarity with version control systems such as Git or TFS.
• Understanding of data modeling principles.
• Hands on experience with ETL tools such as Talend, Informatica, or SSIS.
• Exposure to data virtualization tools such as Denodo
• Working knowledge of SQL, stored procedures, and database table design.
• Familiarity with scripting languages such as Python, Shell scripting.
• Experience with DataOps practices, CI/CD, and observability.

Nice To Haves

• Cloud platform experience (AWS, Azure, or GCP).
• Experience optimizing cost and performance in cloud data warehouses.
• Hands-on experience with Cribl, Apache Kafka, Kafka Connect, Spark Streaming, or Apache Flink
• Experience Data catalog platforms (e.g., Collibra, Informatica IDMC, Alation)
• Experience with Data Observability Platforms  (e.g., Monte Carlo, Data dog, Atlan)
• Talend Certified, AWS Certified, Microsoft Certified, Azure Data Engineer

Responsibilities

• Implement features and enhancements from the data product backlog.
• Partner with Data Product Owners and business stakeholders to understand business and technical requirements.
• Assist in building and maintaining scalable ETL/ELT pipelines.
• Support data ingestion from APIs, relational databases, and flat files.
• Clean, transform, and validate data to ensure quality and consistency.
• Develop and optimize SQL queries for reporting and data extraction.
• Collaborate with data analysts and data scientists to meet analytical requirements.
• Monitor data workflows and troubleshoot data pipeline issues.
• Maintain documentation for data processes and technical solutions.
• Follow data engineering best practices and standards.
• Learn from and collaborate with senior engineers on enterprise initiatives.
• Perform ad hoc data analysis and queries to support business needs.

Benefits

• health, dental, and vision benefits with coverage for families and domestic partners
• vacation
• retirement plans including 401k contributions and matches
• paid holidays
• tuition reimbursement
• bonus eligibility
• sick leave
• disability insurance

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level