Senior Data Engineer, Solutions Architecture

Clearway Energy

San Diego, California

Full Time

Posted May 1, 2026

$110k - $145k

Renewable Energy Development

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Job Description

A Senior Data Engineer responsible for designing, building, and maintaining scalable data infrastructure and pipelines to support energy operations, analytics, and trading activities, utilizing advanced data stack tools and ensuring data quality, security, and collaboration across teams.

Key Responsibilities

Design, deploy, and maintain scalable data infrastructure to support analytics and reporting
Manage Snowflake instances, including performance tuning, security, and capacity planning
Build and orchestrate complex ETL/ELT workflows using Dagster
Develop and maintain dbt models for data transformation and analytics
Implement data validation, testing, monitoring, and governance frameworks
Lead CI/CD processes for data pipelines and analytics applications
Collaborate with cross-functional teams to understand requirements and deliver data solutions

Requirements

Minimum of 4 years of hands-on data engineering experience in production environments.
Bachelor’s degree in Computer Science, Engineering, or a related field.
Proficiency in Dagster for pipeline scheduling, dependency management, and workflow automation.
Advanced-level Snowflake administration, including virtual warehouses, clustering, security, and cost optimization.
Proficiency in dbt for data modeling, testing, documentation, and version control of analytical transformations.
Strong Python and SQL skills for data processing and automation.
At least 3 years of experience with continuous integration and continuous deployment practices and tools, with proficiency in GitLab CI/CD required.
Experience with GitHub Actions is a plus.
Advanced SQL skills, database design principles, and experience with multiple database platforms.
Proficiency in AWS, Azure, or GCP data services, storage solutions such as S3, Azure Blob, or GCS, and infrastructure as code.
Experience with APIs, various data connectors, and formats.
Understanding of data security best practices, including access controls, encryption, and role-based access management.
Practical experience integrating and leveraging large language models (e.g., OpenAI, Anthropic, or open-source models) within data workflows, with awareness of data privacy, prompt injection risks, and responsible AI usage in production environments.
Strong analytical and troubleshooting skills with attention to detail.
Ability to work effectively with both technical and business stakeholders.
Work comfortably in a hybrid work environment, with 2-3 days in office, demonstrating autonomy, a strong work ethic, and a growth mindset.
Ability to create and maintain technical documentation, data dictionaries, and onboarding materials for data assets.
Implement role-based access controls, data encryption, and security best practices across the data stack.
Monitor and optimize cloud infrastructure costs, implement resource allocation strategies, and provide cost forecasting.