Top Remote Data & Analytics Jobs

Lead design and delivery of enterprise Power BI solutions and a Power BI Center of Excellence. Build scalable data models, integrate BI with centralized data platforms and ERP systems, govern BI assets, adopt DevOps and Agile practices, mentor teams, and drive analytics adoption to enable data-driven decisions across the organization.

Leads business intelligence, market analysis, and competitive intelligence for U.S. flat steel products. Develops dashboards, market forecasts, segmentation studies, pricing insights, and competitive databases. Partners with sales, marketing, finance, and production planning to support commercial strategy, customer targeting, business planning, and senior leadership decisions. Tracks steel industry trends, macroeconomic indicators, trade policies, tariffs, and competitor activity while presenting actionable recommendations.

Collects, cleans, validates, and analyzes data from multiple sources. Builds reports, dashboards, and visualizations; writes SQL queries; documents data definitions; checks data quality; and presents findings to technical and non-technical stakeholders. Supports ad hoc data requests and helps client program leaders make informed decisions. The role is fully remote and requires strong communication, analytical, and independent-working skills.

Build analytical frameworks, measurement methodologies, and decision support to drive enterprise decisions across marketing, loyalty, pricing, menu, media, and operations. Mine and integrate customer, transaction, digital, and operational data; develop segmentation, predictive models, and dashboards; lead test-and-learn, incrementality, and forecasting efforts; translate analysis into clear business recommendations and scalable decisioning tools.

Leads competitive intelligence for USAA’s annuity business, analyzing competitors, products, pricing, market trends, filings, and industry developments. Translates insights into strategic recommendations, executive briefings, competitive positioning, and growth initiatives. Manages enterprise-wide research projects, intelligence processes, external agencies, budgets, risk considerations, and a team of analysts. Requires deep annuity and life insurance industry knowledge, strong quantitative and qualitative analysis, executive communication, and leadership skills.

Deliver customer-facing technical training in data engineering and AI through virtual and onsite sessions. Create tailored courses, projects, certifications, and assessments aligned with customer roles, tools, and business outcomes. Partner with Customer Success, Sales, Product, and Content teams to design blended learning paths, drive platform adoption, and improve measurable skills. Support diverse technical and non-technical audiences across time zones, with occasional onsite travel and success metrics tied to customer satisfaction, bookings, and professional services revenue.

Leads the architecture, development, and support of enterprise data warehouses, lakehouses, dimensional models, ETL/ELT pipelines, and governed data products using Microsoft Fabric and related tools. Ensures data quality, security, scalability, performance, and reliability for analytics and reporting. Partners with technical and business stakeholders, documents data solutions, guides architecture decisions, mentors team members, and drives continuous improvement of data engineering standards and practices.

The Epic Business Intelligence Developer creates analytics content for Epic data, configures applications, writes SQL reports, and manages data models and analytics catalogs.

Designs and maintains scalable ETL pipelines, data models, integrations, cloud databases, and healthcare data infrastructure. Ensures security, HIPAA/HITRUST compliance, reliability, monitoring, and documentation while collaborating with product, engineering, and clinical teams. Requires strong SQL and Python expertise, modern data warehousing and orchestration experience, cloud platform knowledge, and familiarity with healthcare interoperability and claims data.

Build and own commercial data models in Snowflake and dbt for ARR, bookings, pipeline, account scoring, ICP fit, upsell, and whitespace analysis. Establish semantic layers, governance, documentation, testing, monitoring, and CI/CD practices. Partner with Sales, Marketing, Finance, and enterprise data teams to deliver trusted self-service analytics, improve data infrastructure, and develop AI-powered automation. This senior individual contributor will own the roadmap and mentor analysts on data modeling and dbt.