Top Senior Analysis Reporting Jobs in Detroit, MI

Build and maintain modern data-centric applications, pipelines, transformations, enrichment processes, provisioning layers, and user interfaces supporting clinical and operational healthcare processes. Analyze clinical data and report trends using cloud, big data, data science, and modern software development practices. Collaborate with Product, Platform, and Architecture teams, mentor Data Engineers, document solutions, manage source control, and research emerging technologies.

Design, build, and operate scalable ETL/ELT pipelines and backend data services using Go. Integrate relational, NoSQL, blockchain, API, web, and social data sources; develop NLP pipelines for text extraction and classification; and support production APIs, dashboards, alerts, and intelligence systems. Collaborate with engineering, data science, and investigations teams on architecture, data quality, lineage, validation, monitoring, and client-facing products.

Leads the data organization across data engineering, analytics, reporting, and data science. Defines data strategy, architecture, governance, quality, and platform roadmaps; manages and develops technical teams; partners with business and engineering leaders; and guides scalable AWS-based data infrastructure, batch and real-time pipelines, and data products that support strategic growth.

Develops and maintains dashboards, reports, data tools, and data infrastructure for Consulting. Analyzes client, project, portfolio, capacity, compliance, and outcomes data to identify trends and support decisions. Maintains data integrity across Salesforce, Resource Hero, Power BI, and related systems; establishes governance standards; trains staff; and manages consulting projects, workflows, budgets, timelines, and deliverables.

Design and deliver modern data platforms, scalable and secure ingestion and transformation pipelines, durable data models, streaming systems, and reporting layers. Partner directly with clients and business stakeholders to translate requirements into architecture, explain tradeoffs, and own delivery outcomes. The role includes production implementation across cloud data platforms, orchestration, governance, real-time technologies, and analytics or AI data consumption.

Own the enterprise data architecture strategy, target-state models, governance standards, and multi-year roadmaps across Microsoft Fabric, Oracle Fusion ERP, analytics, AI, and enterprise applications. Establish data domains, interoperability standards, data products, metadata, lineage, quality, security, and lifecycle controls. Lead architecture reviews, governance decisions, and cross-functional collaboration while guiding engineering, analytics, security, and business teams toward scalable, trusted, business-aligned data capabilities.

Develops healthcare reporting and analytics solutions using Power BI and SQL to improve operational and clinical performance. Responsibilities include gathering requirements, validating data quality, creating dashboards and reports, partnering with data engineering and advanced analytics teams, training users, maintaining documentation, managing reporting timelines, and resolving data or logic issues.

Conducts operations research and advanced analytics to optimize public-sector command performance and reduce costs. Develops optimization, statistical, simulation, regression, mathematical, and decision-analysis models; implements analytical models in Python; performs data analysis; supports software development; assesses operational questions; and prepares decision briefings, reports, presentations, and recommendations for senior leadership.

Conduct forensic analytics for anti-money laundering and financial crime monitoring. Analyze large transactional datasets with SQL and Alteryx, identify suspicious behaviors and emerging typologies, develop and validate detection scenarios, calibrate thresholds, perform lookbacks and segmentation studies, evaluate transaction networks, and support AML investigations, SAR narratives, and regulatory responses.

Own and evolve Worldly’s production data lake, Postgres warehouse, CDC and streaming pipelines, dbt transformations, orchestration, BI access controls, and graph integrations. Maintain reliable, governed analytics infrastructure using Iceberg, Trino, Dagster, Terraform, and AWS. Support production generative AI workflows involving embeddings, similarity search, extraction, and classification. Responsibilities include data quality, monitoring, security, incident response, disaster recovery, schema governance, and collaboration with data science and analytics stakeholders.