Data Engineer I

Center for Energy and Environment•Minneapolis, MN

13h•$83,000 - $87,000•Hybrid

About The Position

We are looking for a Data Engineer to join our Technology team. As a Data Engineer, you will build and maintain data architecture and pipelines supporting various programs and initiatives across CEE, including automated data ingestion processes and dashboards. This role reports to the Director of Information Technologies and primarily focuses on ETL processes: extracting, cleaning, ingesting, and transforming data to meet Analysts' needs. This role will work collaboratively with other Data Engineers to support the Efficient Technologies Accelerator (ETA), as well as broader data needs across the organization.

Requirements

2+ years of hands-on experience programming in Python and SQL, including modifying and maintaining existing code.
Strong understanding of relational databases and practical experience working with a cloud data warehouse such as Snowflake.
Experience developing and maintaining ETL/ELT pipelines, including data extraction, transformation, loading, and validation.
Experience designing and implementing SQL tables, views, queries, and data transformations.
Experience using Git or another version control system.
Familiarity with Microsoft Office 365, especially Excel.
Ability to troubleshoot data and code issues systematically and independently.
Strong attention to data quality, accuracy, and reproducibility.
Strong motivation and interest in applying data and technology to energy efficiency and sustainability sectors.
Ability to work independently and collaboratively in a fast-paced, dynamic environment.
Bachelor’s degree in computer science, analytics engineering, data analytics, data science, or a related field, or equivalent professional experience.
Minimum of 0-2 years of experience in a data engineer or similar role related to data analytics, data engineering, statistics, or a related technical field; internship, co-op, academic project, or applied business experience may be considered.
Foundational SQL skills
At least one analytical or statistical programming language such as Python
Experience using Git or another version control system.

Nice To Haves

Experience with data visualization tools such as Tableau, Power BI, Plotly Dash.
Experience with workflow orchestration tools such as Prefect, Airflow, or similar platforms is preferred.
Excellent written and verbal communication skills, interpersonal skills, and ability to craft clear and compelling deliverables.
Strong organizational and time management skills, with the ability to prioritize tasks and manage multiple projects.
Ability to work effectively in cross-functional teams and on a variety of tasks.
Basic knowledge or interest in energy efficiency and decarbonization is a plus.

Responsibilities

Support the development and implementation of the team’s data architecture, including processes for managing, integrating, and maintaining datasets provided by external partners.
Write, modify, and maintain Python ETL scripts and SQL data models to automate, scale, and optimize data processing workflows.
Build and maintain repeatable processes to combine raw data from multiple sources into clean, searchable datasets housed in cloud data warehouses.
Develop, maintain, and monitor automated data workflows using Prefect or similar workflow orchestration tools, including scheduling, task dependencies, error handling, and troubleshooting.
Develop and implement data validation and QA/QC processes to monitor data integrity, identify discrepancies, and improve data quality.
Troubleshoot and resolve issues across data pipelines and ETL, investigate discrepancies, and work with team members to identify and implement solutions.
Work closely with Energy and Data Analysts to build and enhance data solutions, including interactive dashboards using tools such as Plotly Dash and Power BI, that support analysis, reporting, and decision-making.
Respond to ad hoc data and reporting requests from internal teams, making changes to database structures, schemas, tables, views, queries, and dashboards as needed.
Use Git and established version control practices to manage code changes and collaborate with team members.
Contribute to the continuous improvement and automation of the team’s data workflows and infrastructure.
Facilitate conversations with cross-functional teams to understand reporting, data intake, and data cleaning needs; build queries and views to support these needs.
Maintain, clean, and organize large datasets and repositories to ensure data integrity and accessibility.
Document data processes, transformations, and workflows to improve maintainability and knowledge sharing.
Conduct quantitative analysis to support program evaluation and measure performance.
Contribute to cross-functional projects and assist in the development of technical documentation and deliverables.
Work closely with engineering, research, and program teams to support technical analysis and program implementation.
Other duties as assigned