Top Remote Data & Analytics Jobs in Kansas City, MO

Lead fraud analytics for application fraud detection: identify emerging patterns, design and test real-time defenses, balance risk and customer experience, build dashboards and metrics, and collaborate with Operations, Product, Data Science, and Engineering to reduce fraud losses and improve cardholder experience.

Supports government program data collection, reporting, analysis, forecasting, visualization, and dashboard development. Builds automated reporting solutions, data models, databases, and presentations; performs statistical analysis and interprets findings for agency leadership. Collaborates with federal stakeholders, contractors, and domain experts to improve data collection, identify performance indicators, provide technical support, and train field staff on data tools. The role is remote, with potential future onsite work in Washington, DC.

Provides production database administration and support for mission-critical environments, including performance monitoring, incident response, root-cause analysis, security, and availability. Develops SQL Server database objects, ETL pipelines, dimensional models, data marts, dashboards, and Splunk monitoring solutions. Designs cloud and hybrid database architectures, performs data migrations, validates data integrity, and collaborates with stakeholders on technical requirements and analytics solutions within an Agile environment.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Develops Power BI dashboards, reports, and automated workflows for Learning & Development and strategic management. Analyzes learning, workforce, and operational data to identify trends, measure effectiveness, and support business decisions. Partners with stakeholders to define reporting needs, improve processes, and administer learning technology platforms and LMS tools.

Leads the design and implementation of AI-powered data pipelines, enterprise feature stores, analytics-ready repositories, and self-service data access layers. Builds automated feature engineering, data quality, observability, and governance capabilities for large-scale data science workloads. Partners with Enterprise IT, establishes data availability and quality SLAs, integrates structured and unstructured data sources, and leads teams delivering scalable analytics infrastructure.

Leads enterprise reporting for data quality, governance, compliance, and operational performance. Designs executive dashboards, scorecards, and reporting packages; integrates metadata and quality metrics; aligns definitions and thresholds with stakeholders; oversees incident and remediation tracking; manages vendors, schedules, documentation, and change controls; validates data integrity; automates recurring reports; and escalates risks and compliance issues to leadership.

Build and extend automated enterprise data governance and quality frameworks. Define measurable trust rules, data contracts, validation and certification workflows, metadata, lineage, tagging, and trust scoring across a cloud data platform. Integrate governance checks into developer workflows and Collibra, coach engineering and product teams, and establish organization-wide data trust standards. The role requires strong SQL, BigQuery or comparable warehouse experience, and expertise with data quality or observability tools.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Leads the Sales Analytics and Reporting function and manages Sales Analysts. Oversees dashboards, scorecards, KPI tracking, profitability analysis, business insights, executive reporting, and sales technology platforms. Partners with Sales, Finance, Product, Technology, and other stakeholders to improve performance, profitability, planning, and decision-making. Develops team capability, reporting processes, platform adoption, and analytical effectiveness while translating complex data into actionable recommendations.

Researches market, dealer, customer, competitor, and industry information to identify trends, risks, and opportunities. Develops competitive intelligence, market assessments, SWOT analyses, reports, dashboards, presentations, and actionable recommendations. Maintains intelligence repositories and partners with Sales, Marketing, Product, Analytics, and Strategy stakeholders. This remote role supports regional sales teams, requires core hours aligned to the assigned region, and may involve travel up to 25%.

Build and maintain dbt analytics models using SQL and Jinja, implement data quality tests and freshness checks, create Metabase dashboards, perform ad hoc analysis, and collaborate with finance, product, sales, and customer success stakeholders. The role requires advanced SQL, data modeling, analytics engineering, documentation, statistical analysis, Git-based development, and CI/CD experience, with Snowflake, Python, and data analysis tools preferred.