Top Remote Analysis Reporting Jobs in Detroit, MI

Build and maintain Google Cloud data pipelines and ETL/ELT processes supporting GenAI and RAG solutions. Classify and govern sensitive data using Dataplex and Cloud DLP, enforce access controls, assess AI readiness, and design reusable schemas and data models. Collaborate with engineering, delivery, and client teams to integrate legacy systems, monitor pipeline reliability, conduct data quality testing, document data flows, and proactively identify compliance and delivery risks.

Supports Texas Workforce Commission technology initiatives through business and systems analysis. Documents functional, technical, accessibility, and security requirements; develops user stories, process maps, conceptual and object models, use cases, and architecture diagrams. Creates and executes test cases, ensures requirements traceability, supports legacy-system interfaces, facilitates cross-functional workshops, and assists with project lifecycle artifacts.

The Analytics Engineer develops end-to-end analytics solutions and business applications to streamline Operations and enable digital transformation. Responsibilities include communicating analytics to nontechnical stakeholders, supporting cross-functional supply chain, manufacturing, and quality projects, developing business processes, selecting methodologies and technologies, and improving operational efficiency. The role is fully remote and may involve AI technologies, full-stack development, and optimization modeling.

Develops scalable data models, Databricks pipelines, backend applications, ETL processes, and data ingestion systems. Partners with engineering, product, and business stakeholders on technical roadmaps; monitors and optimizes data systems for performance, reliability, and scalability. Provides technical leadership, mentors junior engineers, conducts code reviews, and builds secure solutions for sensitive healthcare data.

Lead BI reporting and advanced analytics to optimize marketing campaigns and ROI. Build dashboards, manage multi-source data, ensure data governance, provide actionable insights, mentor juniors, and partner with cross-functional teams to guide strategy.

Design, build, and maintain scalable data pipelines, data models, and analytics solutions using Microsoft Fabric and Azure. Develop Lakehouse and Warehouse architectures, Fabric Notebooks with PySpark and Spark SQL, ETL/ELT workflows, and Power BI semantic models. Optimize performance, ensure data quality, security, governance, and regulatory compliance, and collaborate with analysts, data scientists, and business stakeholders to support business intelligence and advanced analytics.

Build and operate scalable cloud data pipelines, warehouses, transformation layers, and ML production systems. Lead data infrastructure architecture, warehouse performance optimization, DataOps monitoring, CI/CD improvements, data quality testing, and large-scale data product delivery. Collaborate across teams, promote data stewardship, and support batch and streaming pipelines while deploying, serving, and monitoring machine learning models.

Build and maintain Databricks data pipelines across bronze, silver, and gold layers. Ingest APIs, logs, billing exports, and reference data; implement attribution logic, governance, data quality monitoring, and cost optimization. Manage Unity Catalog permissions, lineage, refresh schedules, incremental processing, and CI/CD workflows while supporting multi-cloud storage and high-volume caller-identity data.

Own the architecture and technical direction of Northbeam’s data ingestion and integration platform. Design scalable API-based ETL, event-driven and batch processing systems; establish standards for observability, freshness, and failure handling; and guide build-versus-buy decisions. Collaborate across engineering, infrastructure, product, and business teams while mentoring engineers, leading design reviews, and driving complex platform initiatives to completion.

Analyze performance marketing and subscription-funnel data, including acquisition efficiency, conversion, retention, churn, and customer lifetime value. Build automated Domo dashboards and governed reporting pipelines from multiple data sources. Investigate data anomalies, analyze A/B tests, define KPIs, and communicate insights to executives. Partner with marketing, product, engineering, finance, agencies, and BI contractors while independently executing analytics projects and improving reporting workflows.