{"schemaVersion":"jobsearcher.job.v1","id":"89ccfcb9cab297dda3c9a3b9","url":"https://jobsearcher.com/jobs/89ccfcb9cab297dda3c9a3b9","canonicalUrl":"https://jobsearcher.com/jobs/89ccfcb9cab297dda3c9a3b9","title":"Data Analytics Engineer - Chicago","description":"Data Analytics Engineer - Job Description\nChicago based position - not eligible for remote work\n\nWho We Are\nWe are a new technology company that takes the burden out of cross-community workforce collaboration to power up pathways to meaningful employment, mobility, and prosperity. STEAMe’s platform unites all partners to support learners, reduce stop outs, and ensure employers get people with the right skills into the right jobs at the right time.\n\nThe Role\nAs 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.\n\nWorking 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.\n\nThis 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.\n\nKey Responsibilities\n\nPartner with cross-functional teams to understand business objectives and translate them into scalable data models, metrics, and analytics solutions\n\nDesign, build, and maintain data transformations and lightweight ETL pipelines using SQL and Python\n\nDevelop and maintain curated analytics tables and semantic layers to support reporting and dashboards\n\nCreate and manage dashboards and reports in BI tools (e.g., Tableau, Looker, Power BI) for internal teams and external partners\n\nEnsure data accuracy, consistency, and reliability across analytics outputs\n\nSupport and evolve data architecture by collaborating with engineering on source systems, data flows, and integrations\n\nWrite Python scripts for data preparation, automation, and analytics workflows\n\nExperiment with and develop LLM-enabled workflows, including prompt design, to extract insights, summarize data, or support internal analytics use cases\n\nExperiment with AI tools to deliver new methodologies and optimize workflows\n\nDocument data models, pipelines, metrics definitions, and analytics best practices\n\nTroubleshoot data quality issues and proactively identify opportunities to improve data processes and performance\n\nRequirements\n\nBachelor’s degree in Analytics, Computer Science, Engineering, Statistics, Economics, Mathematics, or a related field (or equivalent experience)\n\n3–6 years of experience in analytics, analytics engineering, or a data engineering–adjacent role\n\nStrong proficiency in SQL and Python\n\nExperience building and maintaining data pipelines, transformations, or ETL processes\n\nHands‑on experience with BI and visualization tools (e.g., Tableau, Looker, Power BI)\n\nSolid understanding of data modeling concepts and analytics best practices\n\nAbility to communicate clearly with both technical and non‑technical stakeholders\n\nComfortable working in a fast‑moving startup environment with evolving requirements\n\nPreferred Qualifications\n\nExperience with cloud data platforms (e.g., AWS, GCP, or Azure)\n\nFamiliarity with modern analytics stacks (e.g., dbt or similar transformation tools)\n\nExperience working with SaaS platforms or in edtech / workforce development environments\n\nExposure to data orchestration tools and APIs\n\nExperience using or designing LLM-powered analytics workflows or prompt‑based tools\n\nEnvironmental Job Requirements & Working Conditions\n\nThis position is based in Chicago, IL\n\nSTEAMe is a Hybrid work environment, with 3 days work from home and 2 days in-office work\n\nSTEAMe is committed to building a diverse team and fostering an inclusive culture, and is proud to be an equal opportunity employer. We embrace and encourage our employees' differences in race, religion, color, national origin, gender, family status, sexual orientation, gender identity, gender expression, age, veteran status, disability, pregnancy, medical conditions, and other characteristics.\n\n#J-18808-Ljbffr","company":"Steame","rawCompany":"steame","city":"Chicago","state":"IL","isRemote":false,"isActive":false,"createdAt":"2026-04-09T09:41:44.810Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.01","title":"Business Intelligence Analysts","slug":"business-intelligence-analysts"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Analytics Engineer - Chicago","description":"Data Analytics Engineer - Job Description\nChicago based position - not eligible for remote work\n\nWho We Are\nWe are a new technology company that takes the burden out of cross-community workforce collaboration to power up pathways to meaningful employment, mobility, and prosperity. STEAMe’s platform unites all partners to support learners, reduce stop outs, and ensure employers get people with the right skills into the right jobs at the right time.\n\nThe Role\nAs 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.\n\nWorking 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.\n\nThis 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.\n\nKey Responsibilities\n\nPartner with cross-functional teams to understand business objectives and translate them into scalable data models, metrics, and analytics solutions\n\nDesign, build, and maintain data transformations and lightweight ETL pipelines using SQL and Python\n\nDevelop and maintain curated analytics tables and semantic layers to support reporting and dashboards\n\nCreate and manage dashboards and reports in BI tools (e.g., Tableau, Looker, Power BI) for internal teams and external partners\n\nEnsure data accuracy, consistency, and reliability across analytics outputs\n\nSupport and evolve data architecture by collaborating with engineering on source systems, data flows, and integrations\n\nWrite Python scripts for data preparation, automation, and analytics workflows\n\nExperiment with and develop LLM-enabled workflows, including prompt design, to extract insights, summarize data, or support internal analytics use cases\n\nExperiment with AI tools to deliver new methodologies and optimize workflows\n\nDocument data models, pipelines, metrics definitions, and analytics best practices\n\nTroubleshoot data quality issues and proactively identify opportunities to improve data processes and performance\n\nRequirements\n\nBachelor’s degree in Analytics, Computer Science, Engineering, Statistics, Economics, Mathematics, or a related field (or equivalent experience)\n\n3–6 years of experience in analytics, analytics engineering, or a data engineering–adjacent role\n\nStrong proficiency in SQL and Python\n\nExperience building and maintaining data pipelines, transformations, or ETL processes\n\nHands‑on experience with BI and visualization tools (e.g., Tableau, Looker, Power BI)\n\nSolid understanding of data modeling concepts and analytics best practices\n\nAbility to communicate clearly with both technical and non‑technical stakeholders\n\nComfortable working in a fast‑moving startup environment with evolving requirements\n\nPreferred Qualifications\n\nExperience with cloud data platforms (e.g., AWS, GCP, or Azure)\n\nFamiliarity with modern analytics stacks (e.g., dbt or similar transformation tools)\n\nExperience working with SaaS platforms or in edtech / workforce development environments\n\nExposure to data orchestration tools and APIs\n\nExperience using or designing LLM-powered analytics workflows or prompt‑based tools\n\nEnvironmental Job Requirements & Working Conditions\n\nThis position is based in Chicago, IL\n\nSTEAMe is a Hybrid work environment, with 3 days work from home and 2 days in-office work\n\nSTEAMe is committed to building a diverse team and fostering an inclusive culture, and is proud to be an equal opportunity employer. We embrace and encourage our employees' differences in race, religion, color, national origin, gender, family status, sexual orientation, gender identity, gender expression, age, veteran status, disability, pregnancy, medical conditions, and other characteristics.\n\n#J-18808-Ljbffr","datePosted":"2026-04-09T09:41:44.810Z","dateModified":"2026-04-09T09:41:44.810Z","hiringOrganization":{"@type":"Organization","name":"Steame","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Chicago","addressRegion":"IL","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"89ccfcb9cab297dda3c9a3b9"},"url":"https://jobsearcher.com/jobs/89ccfcb9cab297dda3c9a3b9"}}