Top Remote Analysis Reporting Jobs in Detroit, MI

Designs, implements, and optimizes Salesforce Data Cloud solutions. Responsibilities include configuring data streams, integrating Salesforce and legacy data with MuleSoft or ETL tools, mapping data objects, creating identity resolution rules, building calculated insights with SQL, developing customer segments, configuring activation targets, and managing data governance, privacy compliance, system performance, storage, and usage.

The Relativity Archiving Analyst will archive and purge Relativity workspaces and file shares, ensuring data integrity and documentation processes for approval.

Senior individual contributor owning marketing data domain end-to-end: design, build, and operate data pipelines, models, governance, and certified data products across Microsoft Fabric and Google BigQuery to support marketing measurement, attribution, reporting, and self-service analytics.

Analyzes pricing, promotional elasticity, portfolio mix, and trade terms to support profitable commercial growth. Builds ROI simulation, mix modeling, dashboard, and tracking tools for Sales and Finance. Translates complex data into actionable recommendations, trade guidelines, and revenue strategies while maintaining data integrity and collaborating across cross-functional teams.

Short-term, paid project to export and submit personal financial data from multiple apps. Participants must provide exports from specific financial categories, create two financial artifacts, redact PII on-device using a provided tool, and follow quality and timeline requirements until Final Approval.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

Leads and develops the Data Engineering team while remaining hands-on with scalable pipelines, ETL/ELT processes, data warehouses, integrations, and infrastructure. Establishes architecture, reliability, quality, and performance standards; guides technical strategy; improves automation and monitoring; and partners with Finance and business stakeholders to translate data needs into practical solutions.

Create and validate complex datasets for AI benchmark tasks, including files with malformed records, missing data, truncations, and inconsistent formatting. Define correct final states, write detailed grading rubrics, and assess AI outputs for accuracy and completeness. The role requires exceptional attention to detail, error detection, format reconciliation, accurate documentation, and clear asynchronous communication in regulated or audit-sensitive contexts.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Lead enterprise Master Data Management strategy, architecture, governance, data quality, and integration initiatives across customer, product, supplier, employee, and financial domains. Design data models, hierarchies, matching and survivorship rules, integration patterns, and implementation roadmaps. Advise clients on Oracle and Salesforce ecosystems, lead workshops and executive presentations, guide solution delivery, mentor consultants, and contribute to proposals and statements of work.

Designs, develops, and maintains Databricks-based ETL pipelines, data lake architectures, datasets, and data warehouses supporting reporting, analytics, and AI/ML workloads. Troubleshoots and optimizes Databricks and SSIS processes, maintains SSRS reports, implements data quality controls, migrates legacy systems, and collaborates with business and technical teams. The role also promotes AI-assisted development practices and documents technical procedures.

Designs, builds, and maintains scalable batch and streaming data pipelines in Databricks using Python, Spark, SQL, and Delta Lake. Supports SQL Server, SSIS, and SSRS environments while improving performance, reliability, data quality, and scalability. Integrates enterprise data sources, applies warehousing best practices, and partners with business and IT teams to deliver reporting, analytics, and AI/ML data solutions.