Senior Data Engineer (Remote - US)

Interested in joining a growing company where you will work with talented colleagues, enhance a supportive and energetic culture, and be part of the climate solution? At Energy Solutions, we focus on the big impacts. And we believe that market-based programs can be a powerful force to deliver large-scale energy, carbon, and water-use savings. Since 1995, we’ve harnessed that power to offer proven, performance-based solutions for our utility, government, and institutional customers.

We are currently seeking a Senior Data Engineer to join our Information Systems team to design, develop, and maintain data platforms that support the data needs across Energy Solutions. In this role, the ideal candidate is a passionate and highly skilled professional with expertise in analytics tools and cloud technologies like AWS, Azure or similar technologies. They should be proficient in programming languages such as SQL, NoSQL, and Python, capable of processing large data sets to deliver high-quality, customer-facing data solutions and insights. This unique position is perfect for individuals with technical prowess in data field who want to have an impact on energy efficiency markets and greenhouse gas reductions through our work for major North American utilities and other clients around the country. 

Energy Solutions has a remote-friendly work environment for staff located throughout the United States. We also have offices in Oakland and Orange, California as well as Portland, Boston, New York and Chicago for those that wish to work from one of our offices.  

 Responsibilities include but are not limited to: 

• Build, automate, and manage near-real-time scalable data ingestion pipelines for master data management, deep-learning, and predictive analytics. 
• Build and maintain cloud native big data environments on AWS, that are highly secure, scalable, flexible, and highly performant using appropriate SQL, NoSQL and NewSQL technologies. 
• Lead data governance and data profiling efforts to ensure data quality and proper metadata documentation for data lineage. 
• Provide technical input into build/buy/partner decisions for all components of the data infrastructure. 
• Partner closely with Data Scientists, BI developers, and Product Managers to design and implement data models, database schemas, data structures, and processing logic to support various data science, analytics, machine learning, and BI initiatives. 
• Design and develop ETL (extract-transform-load) processes to validate and transform data, calculate metrics, and model features, populate data models etc., using Spark, Python, SQL, and other technologies in the AWS. 
• Lead data governance and data profiling efforts to ensure data quality and proper metadata documentation for data lineage. 
• Lead by example, demonstrating best practices for code development and optimization, unit testing, CI/CD, performance testing, capacity planning, documentation, monitoring, alerting, and incident response to ensure data availability, data quality, and usability. 
• Define SLAs for data availability and correctness. Automate data availability and quality monitoring and respond to alerts when data delivery SLAs are not being met. 
• Communicate progress across organizations and levels from individual contributor to executive. Identify and clarify the critical few issues that need action and drive appropriate decisions and actions. Communicate results clearly. 

 Minimum Qualifications: 

• Education: A bachelor’s degree in computer science or information technology
• A minimum of 8 years' of job related experience
• Programming Proficiency: High proficiency in programming languages commonly used in ETL development, such as PLSQL, SQL, Python. Ability to write efficient SQL queries, SQL store procedures, develop scripts for data transformations, and utiliz