Top Senior Analysis Reporting Jobs in St. Louis, MO

Designs and leads production-grade batch, incremental, streaming, and real-time data pipelines across Microsoft Fabric and Azure. Builds Delta Lake medallion architectures, dimensional and Data Vault models, CDC and incremental-loading solutions, CI/CD automation, governance, security, observability, and data-quality controls. Supports migrations to Fabric, prepares governed data for AI and RAG workloads, and leads client-facing engineering workstreams, estimates, risk management, mentoring, and operational handover.

Analyze and maintain recruitment, onboarding, workforce, participant, and program-performance data for the NIH DataForce Service Program. Develop trackers, dashboards, reports, and briefing materials; monitor participant lifecycle activities; identify data-quality issues, risks, trends, and process improvements; and support recurring monthly and quarterly analyses. Collaborate with program managers, mentors, coordinators, and government stakeholders while protecting sensitive information and ensuring Section 508 accessibility compliance.

Lead the reverse-engineering and migration of legacy ETL pipelines from SAP BusinessObjects Data Services and JD Edwards into dbt and Databricks architectures. Build automated data validation, maintain SQL Server write-back mechanisms, collaborate with client stakeholders, and lead and mentor a small engineering team. The role requires hands-on expertise in SQL, Python, Spark, orchestration, cloud platforms, and legacy ERP and ETL migrations.

Lead enterprise data-source integrations across process historian, logistics, and procurement platforms. Build Databricks lakehouse Bronze ingestion pipelines and Silver normalization models, configure Fivetran and ODBC connectors, establish cross-system mappings, and validate data architectures with operations, procurement, and transportation stakeholders.

Own PushPress’s data platform, including ingestion, orchestration, cloud warehouse performance, governance, privacy, data quality, monitoring, and AI-ready data foundations. Build reliable pipelines integrating product, payment, and third-party data; establish data contracts, access controls, auditability, and semantic definitions; support real-time analytics and trustworthy reporting. Partner with Engineering, Data, and AI teams while maintaining infrastructure, incident response, documentation, and operational runbooks.

Build and own production data infrastructure for a healthcare AI platform. Responsibilities include REST API ingestion, Azure Event Hubs streaming into Databricks, Delta Lake medallion pipelines, entity resolution, semantic metrics, data-quality instrumentation, reconciliation, schema-drift handling, and troubleshooting source-to-warehouse discrepancies. The role requires strong Python and SQL skills, independent pipeline ownership, and experience with Databricks, Spark, PySpark, streaming, and healthcare-related data is a plus.

Leads quantitative and qualitative market research on international development, AI adoption, institutional demand, funding, procurement, competition, and commercial opportunities. Evaluates AI and data service applications, develops market assessments and strategic recommendations, manages research initiatives, prepares executive presentations, and collaborates with leadership, technical, operational, and business development teams to support market entry and growth.

Build and guide data platform capabilities supporting marketing, finance, analytics, and data science. Develop data collection, integration, scoring, experimentation, analytics, and infrastructure solutions; contribute code, lead cross-functional technical initiatives, improve system resiliency through incident response, and establish engineering standards. Partner with business and technical stakeholders to define strategy and long-term roadmaps.

Owns DeVry University's website measurement ecosystem, including GA4, GTM instrumentation, event taxonomies, data quality, tracking governance, and conversion measurement. Analyzes SEO, AI search visibility, website journeys, acquisition, engagement, and conversion performance using SQL and dashboarding tools. Investigates anomalies and friction, supports experimentation, automates monitoring, and delivers prioritized recommendations. Partners with web, marketing, SEO, technology, analytics, and external teams to improve measurement reliability, digital experience, and prospective student conversion.

Build and support production analytics models using SQL, dbt, BigQuery, Looker, and LookML. Develop governed semantic layers, self-service analytics, automated tests, and reliable datasets for business and AI use cases. Partner with stakeholders to translate ambiguous requirements into reusable solutions, investigate data discrepancies, optimize performance, support platform modernization, and maintain data quality, privacy, and documentation.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.