Top Senior Business Intelligence Jobs in Detroit, MI

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead integration of technology into information systems, design data warehouse and BI capabilities, define data architecture and dictionaries, centralize disparate data, design dashboards, document system architecture, perform data quality and management, and provide solution engineering, pilots, and enablement for analytics and resource management.

Build end-to-end data products and scalable data models for Ford Customer Service. Translate user needs into data requirements, lead analysis, integrate heterogeneous sources, implement governance and privacy controls (CCPA/GDPR), and deliver dashboards and BI solutions using BigQuery, Informatica, Cognos/QlikView to support decision-making and dealer/customer outcomes.

Lead enterprise data governance, quality, MDM, cleansing, validation, reconciliation, and migration efforts to support ERP implementations and large transformation programs. Develop governance frameworks, coordinate data readiness and testing, produce executive reporting and presentations, manage project plans and governance artifacts, and drive stakeholder alignment and change management.

The Business Intelligence Senior Analyst transforms warranty and quality data into actionable insights, develops presentations, and collaborates with various teams to drive decision-making.

Senior BI developer responsible for designing, developing, testing, and maintaining data warehouse and BI solutions. Works with business stakeholders to translate requirements, implements ETL and reporting using BI tools, ensures SDLC compliance, conducts design/code reviews, and supports production systems in a healthcare payer environment.

Transform data into actionable insights by building dashboards, reports, and visualizations. Partner with cross-functional teams and data engineering to ensure data quality, lineage, and AI-ready metadata. Audit datasets, define monitoring rules, document data dictionaries, pilot AI-assisted BI tools, and apply hypothesis-driven analysis to surface insights that inform business decisions.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

The Director of Data and Enterprise Applications oversees the architecture, development, and support of business applications and data platforms, driving digital transformation and ensuring data integrity and accessibility.

Own and operate the Microsoft Fabric and Power BI platform end-to-end: administer tenants, capacities, OneLake, and governance; build secure data integration pipelines and access layers for BI and AI agents; automate CI/CD and platform operations; enforce security and data governance; and translate business requirements into technical designs while liaising between IT, security, and business stakeholders.

Lead GTM strategy and analytics to build headcount/capacity models, territory optimization, quota setting, predictive models, and BI reporting. Partner with Sales, Marketing, Finance, and Data to inform planning cycles, monitor pipeline and productivity, and deliver executive-level insights for growth and investment decisions.

Lead architecture and delivery of enterprise data transformation on the Guidewire Data Platform. Drive design, ingestion/egress, migration performance, and AI-enabled tooling. Facilitate inception and design review sessions, mentor teams, coordinate with partners, and ensure successful data platform adoption and repeatable delivery practices while spending significant time on customer sites.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Partner with stakeholders and engineering to develop BI solutions, perform advanced analysis on structured and unstructured data, identify root causes, and deliver data-driven recommendations and reports using SQL, Power BI, and Python/R to improve operational performance.

Embed as the primary analytics partner on a digital product team to define KPIs, own measurement plans, build PowerBI dashboards, analyze member product behavior and funnels, design and evaluate A/B tests, write SQL/Python for analyses, and translate findings into actionable recommendations for product leaders and senior stakeholders.

Design, build, and support enterprise BI solutions including reports, dashboards, ETL/ELT, data marts, governed datasets and production support. Translate business requirements into technical designs, perform complex data analysis and root-cause investigations, document lineage and runbooks, optimize solutions, enforce data governance, and provide technical leadership or mentorship for large-scale initiatives.

Collect and analyze competitive intelligence and conduct due diligence and investigations on investment candidates and related entities. Design data collection methods, use research, network analysis and AI/automation tools to produce high-quality reports and actionable recommendations for senior stakeholders, and improve workflow productivity.

Lead design and ownership of ZoomInfo's PLG measurement system, define KPIs and leading indicators, analyze end-to-end customer journeys, diagnose growth issues, and influence product investments. Build AI-native, automated analytics workflows, reporting, and monitoring while partnering cross-functionally to prioritize experiments and scale insights that drive adoption, retention, monetization, and expansion.

Design, develop, and maintain BI dashboards, self-service reporting, and predictive analytics for a cloud-based federal case management program. Translate business requirements into technical designs, implement SQL/data transformations, ensure governance and compliance, support AI/ML capabilities, and drive adoption and performance of analytics solutions.

Lead analytics and BI for Digital Product Operations: define product and adoption metrics, build dashboards, ensure data governance and quality, measure ProdOps effectiveness, coach PM/POs, diagnose adoption gaps, and drive interventions that improve product planning and delivery.

Lead Tilt's Business Intelligence function end-to-end: manage a distributed BI team, own reporting data models and semantic layer, build and maintain a metric-and-metadata library with reference SQL, review dbt work and hold quality through code review, prioritize stakeholder requests, and grow team technical and business fluency.

Own and maintain KPI reporting pipelines and business logic, ensure data quality, diagnose KPI changes, perform deep-dive analyses, build dashboards and visualizations, architect data models and curated reporting zones, and partner with Data Engineering and product/marketing stakeholders to enable self-service analytics.

Lead business intelligence efforts to analyze complex data, define KPIs, identify operational inefficiencies, and recommend process improvements. Collaborate with cross-functional teams and executives to implement data-driven strategies, manage improvement projects, monitor resource allocation, and ensure compliance with policies and regulations.

Lead product analytics efforts to define KPIs, build measurement frameworks, analyze customer behavior, and generate insights that influence product and engineering decisions. Partner with Product, Engineering, and Data teams to design event tracking, run experiments, quantify opportunity sizes, and communicate recommendations through clear narratives and visualizations to drive product adoption, retention, and business outcomes.