Top Remote Data & Analytics Jobs

Leads financial and marketing analytics across campaign planning, experimentation, measurement, reporting, and optimization. Owns stakeholder relationships, develops incrementality and ROI frameworks, applies predictive models, defines data requirements, enhances analytical tools and controls, and coaches junior analysts. Partners with marketing, finance, modeling, data, and execution teams to translate complex quantitative insights into actionable investment and growth decisions.

Leads marketing analytics across campaign planning, financial modeling, experimentation, execution support, performance measurement, and ROI optimization. Partners with Marketing, Finance, Modeling, and Data & Analytics teams to develop predictive insights, measurement frameworks, dashboards, and data requirements. Uses analytical tools and platforms to evaluate incrementality, profitability, and campaign effectiveness while maintaining repeatable, auditable processes and communicating findings to senior stakeholders.

Lead design and implementation of large-scale Azure cloud data systems and ETL/ELT pipelines using Databricks, Spark, Snowflake and LLM integrations. Build AI-driven solutions, optimize SQL performance, define architecture and best practices, mentor engineers, collaborate with stakeholders, and drive scalable, secure data platforms for analytics and machine learning.

Supports the enterprise data governance program by developing policies, enabling data ownership and stewardship, governing metadata and data quality, coordinating compliance activities, facilitating stakeholder engagement, tracking governance initiatives, and reporting KPIs. The role promotes adoption of data catalogs, business glossaries, data standards, privacy requirements, retention controls, and governance best practices across business and technology teams.

Architect and own marketing data infrastructure, including Databricks pipelines, Gold Layer tables, semantic models, and ETL/ELT workflows. Build trusted data products for analytics, automation, and AI agents; translate ambiguous business needs into scalable solutions; lead cross-team initiatives; ensure reliability and data quality; mentor engineers and analysts; and develop, evaluate, and monitor production LLM and agent systems using Python and SQL.

Architect and own marketing data infrastructure, including Databricks pipelines, Gold Layer tables, semantic models, and trusted analytics foundations. Lead cross-functional data initiatives, translate ambiguous business needs into scalable solutions, ensure data quality and reliability, and mentor engineers and analysts. Build, evaluate, and monitor production LLM and agent systems, automate marketing workflows with AI, and deliver high-quality Python and SQL solutions supporting Marketing, Sales, and R&D.

Leads Motorsports Data Infrastructure and Data Science teams while owning the strategy, architecture, and delivery of data platforms supporting telemetry, simulation, trackside, analytics, and AI/ML use cases. Responsibilities include managing managers, designing streaming and batch pipelines, productionizing ML models, setting engineering standards, managing Azure and Databricks capacity, protecting sensitive data, and partnering with racing and executive stakeholders. The role remains hands-on in architecture, coding, code review, incident support, and technical problem-solving.

The SI Business Analyst will drive integration between business needs and technical delivery, focusing on insurance and healthcare systems. Responsibilities include capturing requirements, performing gap analysis, designing workflows, and leading cross-functional teams to optimize system performance and support digital transformation initiatives.

Build and maintain dbt data models, SQL transformations, ingestion pipelines, orchestration, and Tableau dashboards in support of HR and enterprise analytics. Own data quality, metric standardization, privacy controls, Row-Level Security, documentation, CI/CD, and troubleshooting from source systems through reporting. Partner with stakeholders to define requirements and KPIs, support workforce forecasting, optimize BigQuery performance, and pilot AI-assisted analytics using Google Gemini.

Analyzes renewal opportunities and account histories, gathers pricing, product, partner, and contract data, and prepares system-derived renewal proposals. Uses Salesforce and Excel to validate information, review documents, test system enhancements, and coordinate with cross-functional teams. Manages assigned regional tasks, organizes findings, and ensures accurate, timely completion in a deadline-driven environment.

Leads database design, administration, performance tuning, security, replication, monitoring, upgrades, and production support across PostgreSQL, Cassandra, Elasticsearch, Redis, and other database platforms. Designs highly available and distributed architectures, supports incident and change management, performs troubleshooting and root cause analysis, and collaborates with global engineering and operations teams. Occasional after-hours work and international travel may be required.

Leads an eight-person analytics engineering team and sets strategy for trusted semantic models, governed data, enterprise BI, AI-powered data access, and production data applications. Oversees data modeling, evaluation datasets, telemetry, LLM routing, governance, security, and self-service capabilities. Partners cross-functionally to establish engineering standards, roadmaps, and measurable business impact while hiring, coaching, and developing team members.