Lead Data Engineer

Posted 2 Days Ago
Hiring Remotely in U.S.
Remote
94K-116K Annually
Mid level
Big Data • Analytics • Energy • Renewable Energy
The Role
Develop and maintain data ingestion pipelines, relational databases, ETL/ELT workflows, cloud resources, data reliability monitoring, and AI-enhanced applications. Integrate LLM APIs and MCP connectors, write Python and R automation code, migrate siloed processes into centralized systems, and collaborate with technical and non-technical stakeholders. The role also supports Azure deployments, enterprise data integrations, dashboards, reporting, and cloud data security.
Summary Generated by Built In

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 simultaneously in a collaborative, evolving environment
  • Strong written and verbal communication skills, including the ability to collaborate with non-technical stakeholders

Preferred Qualifications

  • Hands-on experience with Azure cloud services (Azure SQL, Azure Functions, Azure Blob Storage, or similar)
  • Familiarity with ETL/ELT concepts and data pipeline design patterns
  • Experience with data modeling best practices
  • Experience building lightweight internal web tools or APIs
  • Experience with data visualization tools such as Power BI
  • Familiarity with Salesforce, Workday, or similar enterprise data sources, especially working with their APIs
  • Experience working in a non-profit environment
  • Demonstrated interest in energy, climate, or sustainability sectors

We encourage anyone who is interested in this role to apply, regardless of whether you feel you meet 100% of the qualifications. The top candidates will bring their own unique perspectives, experiences, and backgrounds from a variety of industries along with many but not necessarily all the skills listed above. We offer professional learning and training opportunities to help you develop the skills you may not have had the opportunity to cultivate yet. 

Visa Sponsorship

Please note: At this time, RMI is not able to sponsor employment visas or hire candidates who require visa sponsorship to work in the United States. All candidates must have current, independent authorization to work in the U.S. without present or future sponsorship from RMI. We will update our hiring pages if this status changes. 

Location 

We are a remote-ready company with team members around the globe. Our beautiful and welcoming offices are available for meetings or focused work, whether you are traveling through or living nearby. Our U.S. offices are in New York City; Washington DC; Oakland, California; Boulder, Colorado, and Basalt, Colorado. This role can be located from anywhere in the continental United States. 

We provide you with the essential IT equipment plus a one-time home technology payment and a monthly work from home/commuter allowance to ensure you have a comfortable home office set up and necessary supplies. 

We love seeing each other in person! We occasionally gather for shared time together like retreats and learning experiences. Be ready to travel for occasional in-person meetings (and of course, we cover travel costs). Some roles may require more travel, which will be discussed during the hiring process. 

Compensation 

At RMI, we prioritize fairness in our pay practices. Salaries are determined based on a mix of experience, market benchmarks, and internal equity across similar roles. The salary range of this position is $93,890 - $115,720. New hires typically start toward the lower end of the range, depending on experience and alignment with the role's scope. In addition to base salary, this position includes an annual bonus target of 10% and eligibility for merit-based increases, which are tied to both individual and organizational performance. 

Benefits 

We offer an array of benefits including: 

  • Medical, dental, vision insurance

  • 403b retirement match with immediate vesting

  • Group life, AD&D, and short- and long-term disability

  • Optional voluntary life, AD&D and accident plans

  • Health savings or flexible spending accounts

  • Fertility and hormonal health support

  • Mental health and wellness support

  • Comprehensive leaves of absence (including generous parental leave)

  • Generous paid time off and sick leave

  • Paid sabbatical leave

  • Regional holidays with at least one extended break in each geography

  • Work from home and home technology allowances

  • Learning & development opportunities (LinkedIn Learning and an annual individual professional development budget)

  • Potential for bonuses and merit increases

  • Discount marketplace (gym memberships, pet insurance, etc.)

  • Hybrid / remote work options

  • Team retreats and geographic meetups

  • Rewards and recognition programs

Diversity 

We know that the diversity of our teams makes us stronger as an organization, and RMI is dedicated to the principles of equal employment opportunity as outlined in U.S. federal law. We prohibit discrimination against applicants, interns, and employees on the basis of any legally recognized basis, including but not limited to: age (40 and over), race, color, sex, pregnancy (including lactation, childbirth, or related medical conditions), religion, national origin, ancestry, physical or mental disability, genetic information (including testing and characteristics), sexual orientation, gender expression/identity, uniformed service member status, veteran status, citizenship status, or any other applicable status protected by applicable law. 

RMI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Skills Required

  • 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, including OpenAI or Anthropic APIs and MCP servers
  • Experience writing SQL queries and working with relational databases
  • Exposure to cloud-based data workflows
  • Ability to work across multiple projects in a collaborative, evolving environment
  • Strong written and verbal communication skills and ability to collaborate with non-technical stakeholders
  • Hands-on experience with Azure cloud services such as Azure SQL, Azure Functions, or Azure Blob Storage
  • Familiarity with ETL/ELT concepts and data pipeline design patterns
  • Experience with data modeling best practices
  • Experience building lightweight internal web tools or APIs
  • Experience with data visualization tools such as Power BI
  • Familiarity with Salesforce, Workday, or similar enterprise data sources and APIs
  • Experience working in a non-profit environment
  • Demonstrated interest in energy, climate, or sustainability sectors
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The Company
42 Employees

What We Do

Rocky Mountain Institute (RMI) is a mission-driven organization that accelerates the transition to a low‑carbon energy future through research, practical analysis, and market-based solutions. RMI partners with governments, communities, utilities and industry to design scalable decarbonization strategies—applying geospatial and data-science approaches to identify and eliminate waste methane and other emissions while enabling sustainable energy and climate solutions.

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