Top Entry Level Data & Analytics Jobs in Detroit, MI

Reviews and annotates video content by identifying objects, people, actions, events, and visual details for AI training. Follows project guidelines, checks annotation quality, corrects inconsistencies, flags unclear content, meets productivity targets, and adapts to updated requirements. The role requires independent, detail-focused work, strong written English comprehension, basic computer skills, reliable internet, and personally provided equipment suitable for video annotation.

Own EULER’s data lifecycle, including instrumentation, validation, reconciliation, privacy, anonymization, canonical data modeling, analytics datasets, documentation, and production pipelines. The role requires strong SQL, software engineering practices, independent ownership, skepticism toward data quality, and clear communication. Preferred experience includes GDPR/LGPD, multi-tenant B2B SaaS, dbt, statistics, Cloudflare Workers, Postgres, Parquet, DuckDB, and Bubble.

Investigate and resolve data integration, file processing, and transfer issues. Monitor automated jobs, use SQL and SSIS to validate data, manage SFTP workflows, reprocess files, document integration processes, and collaborate with internal teams to ensure accurate and reliable client and vendor data exchanges.

Maintains accurate CRM data across HubSpot and ServiceNow by processing data requests, entering and cleaning records, resolving duplicates, managing account relationships, supporting bulk uploads, and addressing cross-system data issues. Partners with Sales, Marketing, and IT Development to ensure accurate integrations, workflows, deal data, and adherence to data processes.

Research and monitor political news, government sources, candidates, officeholders, and elections. Update Ballotpedia articles and databases, verify data accuracy, conduct jurisdictional research, write and proofread neutral content, maintain tracking spreadsheets, and collaborate across teams. The role requires strong political knowledge, organization, communication, project management, attention to detail, and flexibility for occasional evening and weekend work.

Manages HR data, analytics, reporting, dashboards, pipelines, integrations, and automation. Supports compensation, performance management, workforce planning, HRIS maintenance, and employee listening initiatives. Builds data models and AI integrations, audits data integrity, develops actionable insights, and presents findings to HR and executive leadership. Requires strong compensation expertise, advanced Excel, HRIS and BI experience, scripting, data modeling, and handling confidential information.

Administer Oracle, SQL Server, and MySQL databases in a fully remote federal environment. Responsibilities include installation, configuration, monitoring, performance tuning, patching, security, backup and recovery, vulnerability remediation, incident response, documentation, compliance, and application deployment support. The role requires collaboration with development and hosting teams, occasional travel, and after-hours or on-call availability. A Public Trust clearance must be obtainable.

Builds and maintains data pipelines and datasets supporting analytics, AI, and modeling. Responsibilities include ingesting healthcare claims and lab data into Snowflake and AWS Iceberg, processing structured and unstructured sources, curating data for AI use cases, implementing medallion architectures, evaluating data quality, and contributing to pilot initiatives using SQL, Python, AWS Glue, Terraform, and Snowflake.

Manage Epic Cogito reporting projects for healthcare organizations by gathering requirements, designing and developing reports, performing testing and validation, and providing post-implementation support. Collaborate with internal and external stakeholders, solve complex problems, and manage multiple projects independently while delivering healthcare IT and analytics solutions.

Build and maintain FinOps data pipelines, BigQuery and dbt models, cost attribution systems, forecasting and anomaly detection models, and cost-versus-revenue analytics. Identify and implement AWS and GCP savings opportunities, automate governance with Python, Terraform, and Lambda, and partner with Engineering, Finance, Product, and leadership on cloud costs, forecasting, reporting, and architecture decisions.