Lead Data Engineer

Job Description

Job Description

RMI is transforming the global energy system to secure a clean, prosperous, zero-carbon future for all. We work with businesses, policymakers, communities and other organizations to identify and scale interventions that will cut greenhouse gas emissions at least 50% by 2030.

RMI is a data-driven organization, and it is critical for there to be a successful and robust data strategy at the organization to improve the impact of our programs. RMI is building a Data and AI Engineering team to enhance access to both internal business systems and external data sources. The Lead Data Engineer will support this initiative, working alongside a multi-disciplinary team, and will be a key contributor to pipelines, infrastructure, and AI-enhanced capabilities. You will report to the Data Engineering Manager on the Strategic Operations team. A successful candidate will be adept at cloud data storage and design, ETL/ELT pipelines, and associated coding languages, with keen attention to detail and a strong desire to support the energy transition.

Key Responsibilities

• Support the development and maintenance of data ingestion pipelines between internal business systems (e.g., Workday, Salesforce)
• Support the development of internal AI-enhanced applications, integrating LLMs via API and MCP
• Assist in building and maintaining relational databases, including MySQL and PostgreSQL schemas, to support internal dashboards, applications, and reporting
• Help implement data reliability and monitoring features across existing data flows
• Deploy and manage Azure cloud resources (database, storage, web app, function app) based on project needs and templates defined by senior staff
• Assist with the development testing, and deployment of various connectors (i.e., MCP servers, APIs) for general purpose AI tools (i.e., ChatGPT, Claude)
• Write clean, reusable code primarily in Python and R to automate data processing tasks and support analytical workflows
• Collaborate with operations staff and non-technical stakeholders to develop a strong working knowledge of data processes and upstream/downstream impact
• Assist in migrating siloed or manual data processes into centralized, accessible systems
• Work with the IT team to ensure security and fidelity of cloud data services

Minimum Qualifications

• 3-5 years of professional or internship experience in data engineering, data science, or a related field

• Proficiency in Python for data processing, scripting, and automation

• Working knowledge of R for data analysis and statistical tasks

• Familiarity with Git or similar version control technology

• Working knowledge of integrating LLM APIs (e.g., OpenAI, Anthropic) into data workflows or applications, including via MCP servers

• Experience writing SQL queries and working with relational databases

• Exposure to cloud-based data workflows; familiarity with Microsoft Azure is a plus

• Comfort working across multiple projects...