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

Design, build, and maintain scalable data pipelines, lakes, and infrastructure using Databricks, Spark, Python, and AWS. Collaborate with ML engineers, data scientists, and analysts to deliver data products, ensure data quality and governance, implement DevOps/SDLC practices, mentor junior engineers, and evaluate new data technologies.

Architect, build, and maintain Snowflake-based ELT pipelines and production data models. Implement observability, data quality, and governance; optimize cost and freshness. Partner with Analytics, Product, and Engineering, use dbt/CI-CD and AI-assisted tooling, and participate in reviews and architecture planning to support analytics, BI, and ML.

Design and maintain scalable dbt data models and Looker dashboards; partner with Finance, Product, and GTM to translate requirements into analytics solutions; ensure data quality with Data Engineering; perform analyses, forecasting, and QA to deliver trusted reporting and drive analytics initiatives.

Design, build, and maintain enterprise Power BI dashboards and data models. Integrate multiple data sources, write DAX, ensure data quality and performance, support stakeholders with requirements, documentation, governance, and ad hoc analytics to enable operational and executive decision-making.

Lead and grow a client-facing analytics team to transform measurement from reporting to strategic advisory. Define measurement strategy, develop scalable frameworks, advise executives, drive vertical analytics, partner with Product and Data teams, and embed AI to improve insight generation and operational efficiency.

Design, build, and operate the credit fund's end-to-end data and automation stack. Implement deal workflow, ingest borrower financials and payment telemetry, develop Python credit scoring and forecasting models, ship audit-grade investor and borrower dashboards, enforce security and auditability, and move into portfolio monitoring and underwriting while presenting results to LPs and borrowers.

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.

Analyze user behavior, feature adoption, and retention across a B2B SaaS platform to generate evidence-based product insights. Track journeys, run cohort and funnel analyses, support A/B testing, define product KPIs, ensure data accuracy, and provide structured recommendations to inform roadmap and improve adoption and retention.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

Lead architecture and evolution of Cardlytics' AWS-based data compute platform and lakehouse. Define standards for batch, streaming, ML, and AI workloads; build semantic layer, feature store, and governance. Partner with analysts and engineers, drive CI/CD (Terraform, GitHub Actions), monitoring, security, cost governance, and incident response while mentoring teams and shaping platform strategy.