Scope of Position
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. We provide low-cost health & wellness coverage for employees and their eligible dependents.
- Rewarding 401k.We provide 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 $120,800 to $201,300 annually. We generally base our salary decisions on factors including but not limited to, relevant work and leadership experience, education, demonstrated performance, internal equity, and in some cases, geographic location.
Scope of Job:
The Principal Engineer, Data Platform plays a pivotal role in shaping and delivering the company’s data architecture vision. This position leads the design and implementation of a modern cloud data platform, spanning infrastructure, data pipelines, and analytics-ready data products. Owning the end-to-end flow of data from source systems through Snowflake to business consumption, the role partners closely with engineers, product leaders, and business stakeholders to deliver scalable, reliable, and high-value data solutions.
As a senior technical leader, this individual influences architectural direction through deep expertise, strong partnership, and credible leadership. They help define and evolve enterprise data architecture standards, translate strategic vision into actionable designs, and contribute meaningfully to architectural decisions across the organization. The role also strengthens the broader architecture community by improving processes, governance, and engineering quality standards. Blending architecture, platform engineering, and analytics engineering, the Principal Engineer brings a holistic approach to delivering modern data solutions that support analytics, integration, and reporting needs. Working cross-functionally with SAP Analytics Engineers, Integration Engineers, Analytics and Insights Engineers, Product Management, and business stakeholders, this role turns strategy into practical solutions that drive measurable business value.
This role has no direct reports but plays a critical role in influencing business and Digital Technology decisions. The individual is expected to shape direction through strong credibility, strategic insight, and trusted advisory relationships, while also serving as a highly skilled mentor.
This position is Hybrid based in San Diego, CA (Rancho Bernardo). Hybrid is three days a week in office, typically Tuesday, Wednesday, and Thursday.
Responsibilities
- Designs and Implements cloud-native data integrations using APIs and AWS services (S3, Glue, Lambda) to bring data into Snowflake from various sources. This role informs, then implements architecture patterns defined by the Data Architect and within standards and guidelines set by the Data Engineering Manager
- Designs, builds, and maintains data transformation models using dbt, creating dimensional models, data marts, and business logic based on specifications from SAP Reporting Analysts and business stakeholders
- Manages Snowflake platform infrastructure including environment setup, performance optimization, cost management, security configuration, and access controls
- Leads cross-functional collaboration and aligns engineering work with business goals by working with business stakeholders, product management, analytics, governance, architecture, and data engineering. Surfaces cross-team decisions to the inform the Principal Architect and Data Engineering Manager as appropriate.
- Applies established standards and criteria in the implementation of data quality frameworks, testing, monitoring, and alerting to ensure data accuracy and pipeline reliability across the platform.
- Contributes to and implements the vision for Data Architecture, translating business requirements into techpriorities.maps; presents progress, risks, and trade-offs to leadership and non-technical business audiences; and partners with Product Management to shape data platform capabilities aligned to business priorities
- Performs data integration tasks and partners with Reporting Engineers to optimize data models for visualization
- Documents data models, lineage, and technical architecture to support data governance initiatives
- Other duties as assigned
Supervision of Others: This role does not supervise any direct reports but has significant influence inside the business and Digital Technology. This role is seen as a highly skilled mentor.
Working Conditions: 95% of time is spent in the office environment utilizing computers (frequent use of various Microsoft software/programs), phones, and general office equipment. 5% of time is spent outside of the office visiting vendors’ and/or internal customers’ sites in addition to attending various conferences and meetings.
Fiscal Responsibilities: May contribute to the Data Engineering budget.
Qualifications
- Education: Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field.
- Core Experience: 8+ years in data engineering or data platform roles, with a proven track record of delivering production-grade data platforms and leading technical teams.
- Cloud & Data Warehousing:
- High proficiency with AWS cloud computing environments and associated data services.
- Deep experience with cloud data warehouses (Snowflake strongly preferred).
- Engineering & Development:
- Languages & Frameworks: Expert-level Python (scripting and data processing) and dbt (transformations, data modeling, and documentation).
- Database Design: Mastery of SQL (complex queries, optimization, database design), dimensional modeling, star schemas, and data warehouse design patterns.
- Data Architecture Practices: Advanced knowledge of change data capture (CDC), slowly changing dimensions (SCD), and incremental loading patterns.
- DevOps & Infrastructure:
- Proficiency with Git version control and modern CI/CD practices.
- Hands-on experience with Infrastructure as Code (IaC) tools (Terraform, CDK, CloudFormation, or Ansible).
Preferred Qualifications
- Experience with workflow orchestration tools (Airflow, Dagster, Prefect).
- Exposure to SAP S/4HANA, SAP HANA, or enterprise ERP environments.
- Experience operating within Agile/Scrum frameworks (sprint planning, retrospectives).
Key Competencies & Scope of Work
- Technical Leadership & Execution:
- Translates data architecture visions, business requirements, and technical specifications into scalable, production-grade solutions.
- Leads technical design discussions, defends proposals in architecture reviews, and aligns infrastructure needs (performance, cost, reliability) with business KPIs.
- Conducts thorough code reviews to ensure maintainability, performance optimization, and quality, while mentoring junior engineers.
- Governance & Quality Assurance:
- Embeds data quality testing and validation frameworks directly into system designs.
- Implements data governance practices, including data lineage, metadata management, and classification standards.
- Leverages data catalog platforms and Jira for transparent project tracking and metadata management.
- Problem Solving & Collaboration:
- Drives root-cause analysis for technical incidents, communicating remediation plans clearly to both technical and non-technical stakeholders.
- Demonstrates a versatile, self-starter mindset—effortlessly shifting between architecture, platform engineering, and analytics engineering in a growing, fast-paced environment.
- Uses strong interpersonal and influence skills to build consensus across broad stakeholder groups while keeping leadership informed of progress, blockers, and trade-offs.
Working Conditions & Physical Demands
- Environment: 100% office-based environment utilizing standard office equipment (computers, phones, Microsoft Office suite).
- Physical Requirements: Ability to sit, stand, or walk for extended periods while operating computer equipment and reviewing digital documentation.