Top Senior Data & Analytics Jobs in St. Louis, MO

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

Serve as a strategic client-facing advisor for Zeta Data Cloud solutions: demo products, support audience curation, audit accounts, identify intelligence-driven opportunities, train client teams, contribute client feedback to the product roadmap, and support RFPs to drive adoption and growth for agency partners.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

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.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.