Data Engineering Manager

Deriva Energy•Charlotte, NC

1d•Onsite

About The Position

Overview Deriva Energy is a leading Independent Power Producer in the US renewables market, with over 6.5GW of operating or under construction wind, solar and storage projects across the country. Formerly the division of Duke Energy, Deriva is now backed by Brookfield Renewable and is poised for dynamic growth across its wind, solar, and storage portfolios. Join a dynamic team committed to excellence and innovation who envision a future of energy independence using resilient, carbon-free generation. We offer competitive compensation, comprehensive benefits, and the opportunity to make a significant impact on the rapidly evolving renewable energy industry. Deriva empowers customers with innovative clean energy solutions that strengthen communities and serve future generations. We are looking for an experienced and dynamic Data Engineering Manager to lead and grow a high-performing team responsible for designing, building, and maintaining scalable data platforms and pipelines. This role blends technical leadership, people management, and strategic thinking to ensure data is reliable, accessible, and impactful across the organization. You will partner closely with analytics, data science, product, and business teams to deliver data solutions that drive decision-making, operational efficiency, and innovation.

Requirements

Bachelor’s degree in Information Technology, Computer Science, or related field (or equivalent experience)
Six (6) years or more of progressive experience in data engineering, including at least two (2) years or more of direct reports/leadership

Nice To Haves

Master's degree in Information Technology, Computer Science, or related field (or equivalent experience)
Eight (8) years or more of data engineering industry working experience
Strong experience with modern data stacks such as: Cloud platforms (AWS, Azure, or GCP) Data warehouses (Snowflake, BigQuery, Redshift, or similar) Orchestration tools (Airflow, Dagster, Prefect, or similar) ETL/ELT tools (dbt, Stitch, Fivetran, or similar) SQL and at least one programming language (Python preferred)
Two (2) years or more of hands-on experience in Spark/PySpark handling big data within an enterprise big data platform
Proven ability to translate business problems into technical solutions
Strong communication skills with both technical and non-technical audiences
Experience with streaming data (Kafka, Kinesis, or similar)
Experience with data governance, data quality, and observability tools
Experience working in fast-paced or scaling environments
Experience partnering closely with data scientists and analytics teams

Responsibilities

Lead, mentor, and grow a high-performing data engineering team, fostering a culture of accountability and continuous improvement.
Define and execute the strategy for scalable, reliable, and secure data platforms and pipelines.
Oversee the design, development, and maintenance of ETL/ELT processes, data models, and infrastructure.
Ensure data quality, system reliability, performance optimization, and cost efficiency.
Partner with analytics, data science, product, and business teams to deliver impactful, data-driven solutions.
Establish and uphold data governance, security, and compliance standards.
Develop and manage the data engineering roadmap aligned with organizational goals.