Top Remote Data & Analytics Jobs in Kansas City, MO

Manage end-to-end data operations, including collection, processing, delivery, pipeline optimization, and data quality monitoring. Collaborate with engineering, product, and operations teams to improve data workflows, identify inefficiencies, and implement scalable solutions. Analyze data to provide actionable insights for decision-making and AI model development while communicating technical issues to non-technical stakeholders.

Designs, develops, and maintains scalable ETL pipelines, data lakes, warehouses, and integrated data solutions. The role includes requirements analysis, Agile collaboration, testing, debugging, documentation, cloud data engineering, and optimization of reliable and performant systems. It requires strong Python, SQL, database, distributed processing, data engineering, software development, and cloud platform skills, along with effective communication and problem-solving abilities.

Processes and validates financial, payroll, ledger, time-tracking, expense, project, and operational data. Converts information into accurate workbooks, templates, reports, and organized deliverables while maintaining employee, project, and expense records. Researches relevant company and industry information, organizes audit documentation, supports interview qualification summaries, and manages multiple data requests and deadlines in a remote environment.

Leads supply chain analytics, reporting, automation, and Power BI solutions while managing product readiness portfolios for launches and product changes. Coordinates cross-functional deliverables, governance forums, SKU readiness, risk escalation, documentation, and milestone tracking across commercialization projects. Translates business needs into scalable analytics and digital solutions, communicates insights, and drives stakeholder adoption and operational improvements.

Build and operate data-intensive web products and APIs, extend high-throughput ETL pipelines and scrapers, ensure reliability/observability, design self-scaling services, participate in code review, and collaborate across product, data, and infrastructure teams to meet production SLAs.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

Analyzes, integrates, and visualizes complex datasets to support enterprise strategy and continuous improvement. Develops Snowflake and Azure data solutions, gathers and documents requirements, writes Agile user stories, coordinates business and IT stakeholders, and ensures data quality through process documentation, root-cause analysis, testing, and incident support. Works independently while influencing departmental strategy and may provide occasional production support during nights or weekends.

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.

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

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.