Top Remote Data & Analytics Jobs in Detroit, MI

Designs and leads scalable, secure, and cost-efficient Snowflake data platforms supporting enterprise analytics, operational reporting, and generative AI applications. Serves as the technical authority for data architecture, modeling, lakehouse design, Snowflake services, dbt transformation frameworks, and Python/Snowpark development. Provides hands-on architectural leadership while influencing executive-level technology strategy.

Designs scalable data models, optimized SQL queries, analytics infrastructure, semantic layers, and data applications. Partners with data science, product, engineering, and business teams to enable dashboards, self-service analytics, reporting, and enterprise data-driven decision-making. The role also establishes analytics engineering best practices, improves developer experience, and supports secure, compliant data warehousing.

Provides operational support for fundraising and business systems through recurring data maintenance, duplicate remediation, bulk uploads, record merges, data quality initiatives, and user support. Responds to ServiceNow requests, creates documentation and training resources, tests system enhancements, and recommends process improvements. The role also supports data validation, reconciliation, reporting, and automation using programming and AI while escalating complex issues appropriately.

Lead business intelligence strategy across product, clinical, commercial, finance, and engineering teams. Build measurement frameworks, semantic layers, reporting solutions, and visualizations that demonstrate business value and support data-informed decisions. Own the data lifecycle from ideation through client-facing delivery, ensure data governance and integrity, and translate complex datasets into actionable insights. Collaborate on scalable data architecture and apply statistical methods, advanced analytics, and emerging AI-driven BI capabilities.

Lead growth analytics for Zendesk’s product-led growth motion, guiding a team of analysts and partnering with Product, Engineering, Sales, Marketing, and Data teams. Define funnel metrics, measurement plans, experiments, and instrumentation across acquisition, activation, conversion, retention, and expansion. Analyze customer behavior using segmentation, cohorts, funnels, experimentation, and statistical methods. Improve self-service reporting, dashboards, metric definitions, reusable datasets, and analytics capabilities while coaching analysts and influencing senior stakeholders.

Analyzes and prepares customer data for successful migration to ServiceTitan. Works directly with customers to understand source databases, identify data issues, interpret database structures, and map data to ServiceTitan’s model. Writes queries to correct, reformat, and transfer data while coordinating with engineers, implementation teams, and onboarders. Manages shifting priorities, deadlines, project updates, and cross-functional communication to ensure accurate, timely data delivery.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.

Design, build, and maintain scalable big data pipelines, architectures, distributed databases, and storage systems. Use Python and frameworks such as Hadoop, Spark, or Flink for data integration, transformation, and processing. Ensure system performance, availability, security, governance, and data quality while collaborating with cross-functional teams and documenting technical solutions.

Design and implement scalable, secure enterprise data solutions on Databricks and Azure using Delta Lake and Medallion Architecture. Lead and mentor data engineering teams; define integration patterns, governance, security (Unity Catalog, RBAC, masking, row/column-level security), and CI/CD/IaC practices. Ensure data quality, lineage, monitoring, and optimize Spark/Delta workloads for performance and cost while aligning solutions with business needs.

Deliver recurring and ad hoc commercial analytics, client reporting, performance-guarantee calculations, dashboards, and value measurement. Define and govern metrics, validate data, improve documentation and workflows, and automate repeatable processes. Partner with Client Success, Commercial, Finance, Product, and Analytics teams to translate complex questions into actionable insights, client-ready narratives, and recommendations that strengthen client relationships and inform business strategy.