Top Remote Analysis Reporting Jobs in St. Louis, MO

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.

Lead GTM data governance and strategy to improve Salesforce and GTM system data quality, ownership, and usability. Define KPIs linking data quality to pipeline/forecast accuracy, drive adoption of standards and scorecards, prioritize data improvements, lead cross-functional implementations, and build a team to scale revenue-impacting data practices.

The Enterprise Data Architect will design and govern data architecture, create enterprise data models, and ensure data consistency across various systems.

Deliver sales reporting, data preparation, dashboard updates, and analysis to support sales intelligence. Maintain data accuracy across the warehouse and CRM, build Power BI visuals, execute ETL processes, and translate insights for non-technical stakeholders.

Own and architect large-scale data pipelines, orchestration, and integrations. Drive IaC strategy (Terraform), third-party API and AI/LLM tool integrations, build export pipelines and internal tooling, mentor engineers, and align cross-team technical strategy for reliable, scalable data infrastructure.

Drive enterprise BI and analytics: partner with Data Engineering to improve data quality, align analyses to product and business strategy, produce audience-focused storytelling and recommendations, detect statistically significant trends, and support cross-functional teams to enable data-driven decisions at petabyte scale.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Build and maintain cloud cost monitoring, alerting, and optimization tooling. Develop automation, cost allocation/tagging, data pipelines, dashboards, and integrations with billing APIs. Support FinOps processes, implement cost guardrails, troubleshoot cost systems, participate in on-call rotation, and collaborate with senior engineers and product teams to drive cost-efficient infrastructure and reporting.

Lead design and execution of an enterprise data governance framework: set policies for data quality, metadata, lineage and privacy; run governance councils; operationalize data ownership and stewardship; implement data cataloging; embed controls in pipelines; ensure compliance and drive organization-wide adoption and change management.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.