Top Remote Data & Analytics Jobs in Ann Arbor, MI

The Senior Data Engineer will design and implement lakehouse architectures, optimize ClickHouse deployments, develop ETL/ELT pipelines, and create data models to support analytical and operational functions.

Support maintenance and quality of proprietary datasets, oversee daily research operations, implement workflows, communicate manager priorities, mentor team members, and help improve efficiency and quality metrics.

Support data-driven operations by sourcing, integrating, validating, and transforming data; build and maintain dashboards, agency scorecards, and reports; analyze KPIs to identify improvement and cross-sell opportunities; measure campaign effectiveness; ensure data quality; partner with stakeholders and technology teams; support monthly reviews and ad-hoc analytics requests.

The Lead Implementation Specialist is responsible for data integration, reporting, and visualization, ensuring compliance, facilitating client support, mentoring, and driving continuous improvement in data processes.

Manage voter contact platforms and related datasets for Party At The Polls. Support peer-to-peer texting, event signup platforms, and CRM operations; build workflows and reporting; collaborate with Communications; maintain forms and data for mail/phone outreach; assist partner-facing platform management and program impact reporting.

You will analyze data, support business teams with insights, enhance dashboards, and manage stakeholder relationships to improve operational efficiency.

Build, optimize, and maintain web analytics data and reporting. Deliver weekly reports and insights, perform deep-dive analyses, recommend website optimizations, partner with paid digital and email teams, and ensure accurate Adobe Analytics implementations.

Maintain and ensure database accuracy, backups, security, and integrity. Develop and implement data standards and procedures, coordinate data collection, monitor compliance, troubleshoot data issues, and collaborate with IT to optimize data management.

Lead and execute applied research on law school access, affordability, and outcomes. Manage and clean data, run advanced statistical analyses, produce tables/visualizations and technical reports, maintain research tools, advise internal and external stakeholders, and present findings at conferences.

Lead scaling of Arbital's AWS/Databricks lakehouse and Spark pipelines, implement actuarial healthcare calculations, own Airflow orchestration and CI/CD, ensure data quality and HIPAA-compliant PHI handling, partner with data scientists to deploy ML models, and set platform architecture and engineering standards.