Data Engineering Lead [Hybrid]

About Us:

EDF power solutions North America has been providing clean energy solutions throughout the U.S., Canada, and Mexico since 1987. We are a market-leading independent power producer and service provider, serving utilities, corporations, industries, communities, institutions, and investors with reliable, low-carbon energy solutions that help meet growing demand.

From developing and building scalable wind (onshore and offshore), solar, storage (battery and pumped storage hydro), smart EV charging, microgrids, green hydrogen, and transmission projects, to maximizing performance and profitability through skilled operations and maintenance and innovative asset optimization, our teams deliver expert solutions along the entire value chain—from origination to commercial operation.

Be a part of an innovative and collaborative team environment that fosters our goal of delivering renewable solutions to lead the transition to a sustainable energy future.

Benefits & Perks: 

EDF power solutions offers best-in-class employee benefits, including the following:

• Competitive bonus incentives. This position is eligible for our annual bonus program.
• Comprehensive health coverage. EDF power solutions USA provides low-cost health & wellness coverage for employees and their eligible dependents.
• Rewarding 401k. EDF power solutions provides a generous matching contribution.

We are also proud to offer:

• Favorable paid time off programs, including paid parental leave after one year of service.
• Rewarding learning & career development and advancement opportunities.
• Supportive mentorship & buddy programs.

Salary Range: The full pay range for this role is$118,400 - $197,300 annually. We generally base our salary decisions on factors such as internal equity, candidate work and/leadership experience, educational credentials, and in some cases, candidate work location.

Scope of Job: The Data Engineering Lead oversees and actively contributes to our data engineering function, leading a team of data engineers while maintaining hands-on involvement in designing and implementing scalable data solutions. This role combines technical leadership with direct contribution to data pipeline development, ensuring high-quality data infrastructure that powers analytics and decision-making processes across the organization. The position includes team leadership responsibilities without fiscal or HR management duties.

Responsibilities:

• Team Leadership & Development
  • Provides guidance on the daily work and mentors a team of data engineers, providing technical guidance and development.
  • Contributes to the hiring process by evaluating candidates, conducting technical interviews, and helping to build a high-performing data engineering team.
  • Champions data-driven decision making throughout the organization.
• Technical Implementation & Architecture 
  • Contributes to the design and implementation of scalable data pipelines, following architectural standards defined by the Principal Data Architect
  • Implements and maintains scalable data pipelines using AWS native services, Informatica, DBT, and Snowflake
  • Optimizes database performance and data pipeline efficiency.
  • Implements data quality frameworks and ensures data integrity across platforms in collaboration with Enterprise Data Governance teams.
• Project Management & Stakeholder Collaboration
  • Partners with product owners, Data Governance teams and stakeholders to manage the data engineering backlog, including story refinement, sprint planning, and prioritization of deliverables.
  • Drives cross-functional collaboration with data science, analytics, and business teams to translate requirements into technical solutions.
  • Provides regular reporting on team deliverables and technical roadmaps to leadership.
• Process & Standards Development
  • Establishes data engineering best practices, standards, and governance procedures.
  • Creates and maintains comprehensive documentation for data models, pipelines, and processes.
  • Evaluates and recommends new technologies to enhance data capabilities.
• Other duties as assigned 

Supervision of Others: provides guidance on daily work to 3 to 8 employees.

Working Conditions: 95% of the time is spent in the office environment, utilizing computers (frequent use of various Microsoft software/programs), phones, and general office equipment. 5% of the time is spent outside of the office visiting vendors’ and/or internal customers’ sites in addition to attending various conferences and meetings. 

Fiscal Responsibilities: none

Education/Experience:

• Bachelor's degree in computer science, engineering, or related field (or equivalent experience), required.
• Advanced degree in Computer Science, Data Engineering, or related technical field, preferred.
• 5-7 years of experience in data engineering roles, with demonstrated leadership experience.
• Experience with CI/CD pipelines for data engineering workflows
• Experience in Infrastructure as Code (IaC) framework (Terraform, AWS CDK)
• AWS certifications (such as AWS Certified Data Analytics - Specialty), preferred.
• Experience with real-time data processing and streaming architecture, preferred.
• Experience leading technical teams and developing technical skills, preferred.

Skills/Knowledge/Abilities:

• Strong hands-on expertise with AWS native services
• Advanced SQL skills and experience with dimensional data modeling
• Proven record of accomplishment designing and implementing enterprise-grade data pipelines and ETL/ELT processes
• Data transformation frameworks (Informatica, DBT), preferred.
• Snowflake data platform, preferred.
• Data visualization tools (PowerBI, QuickSight), preferred.
• Proficiency in Python, Scala, or similar programming languages, preferred.
• Excellent communication skills with ability to translate between technical and business contexts.
• Strong analytical problem-solving abilities and attention to detail
• Deep understanding of data architecture principles and best practices
• Knowledge of data quality frameworks and data integrity concepts
• Ability to manage technical backlogs and prioritize deliverables effectively.
• Capability to work collaboratively across multiple teams and functions.
• Experience with enterprise-scale data transformations and migrations, preferred.
• Experience in the energy sector, particularly renewable energy, preferred.
• Knowledge of data governance frameworks and compliance requirements, preferred.
• Understanding of agile development methodologies, preferred

Physical Requirements: Ability to work in a standard office environment.