Data Analytics Engineer - Job Description
Chicago based position - not eligible for remote work
The RoleAs a
Data Analytics Engineer at STEAMe, you will sit at the intersection of analytics, data engineering, and emerging AI-powered workflows. You'll be responsible for building reliable data pipelines, transforming data for analysis, and delivering high-quality dashboards and reports that drive product, operational, and customer insights.
Working closely with product, engineering, customer success, and business stakeholders, you'll own data transformations, support analytics architecture, and help evolve how STEAMe uses data - including experimenting with LLM-assisted analysis and prompt-based workflows to surface insights more efficiently.
This is an excellent opportunity for someone who enjoys working across the full data lifecycle - from ingestion and modeling to visualization and insight delivery, - in a fast-paced startup environment.
Key Responsibilities- Partner with cross-functional teams to understand business objectives and translate them into scalable data models, metrics, and analytics solutions
- Design, build, and maintain data transformations and lightweight ETL pipelines using SQL and Python
- Develop and maintain curated analytics tables and semantic layers to support reporting and dashboards
- Create and manage dashboards and reports in BI tools (e.g., Tableau, Looker, Power BI) for internal teams and external partners
- Ensure data accuracy, consistency, and reliability across analytics outputs
- Support and evolve data architecture by collaborating with engineering on source systems, data flows, and integrations
- Write Python scripts for data preparation, automation, and analytics workflows
- Experiment with and develop LLM-enabled workflows, including prompt design, to extract insights, summarize data, or support internal analytics use cases
- Experiment with AI tools to deliver new methodologies and optimize workflows
- Document data models, pipelines, metrics definitions, and analytics best practices
- Troubleshoot data quality issues and proactively identify opportunities to improve data processes and performance
Requirements- Bachelor's degree in Analytics, Computer Science, Engineering, Statistics, Economics, Mathematics, or a related field (or equivalent experience)
- 3-6 years of experience in analytics, analytics engineering, or a data engineering-adjacent role
- Strong proficiency in SQL and Python
- Experience building and maintaining data pipelines, transformations, or ETL processes
- Hands-on experience with BI and visualization tools (e.g., Tableau, Looker, Power BI)
- Solid understanding of data modeling concepts and analytics best practices
- Ability to communicate clearly with both technical and non-technical stakeholders
- Comfortable working in a fast-moving startup environment with evolving requirements
Preferred Qualifications
- Experience with cloud data platforms (e.g., AWS, GCP, or Azure)
- Familiarity with modern analytics stacks (e.g., dbt or similar transformation tools)
- Experience working with SaaS platforms or in edtech / workforce development environments
- Exposure to data orchestration tools and APIs
- Experience using or designing LLM-powered analytics workflows or prompt-based tools
Environmental Job Requirements & Working Conditions
- This position is based in Chicago, IL
- STEAMe is a Hybrid work environment, with 3 days work from home and 2 days in-office work
- The pay range for this role is: $120,000 - 130,000. This salary range represents our target hiring range. Final compensation will be determined based on a variety of factors, including experience, skill set, and alignment to the role's scope and level.
