Top Remote Senior Level Data & Analytics Jobs

The Senior Client Data & Analytics Lead guides clients in developing data capabilities, coaching their teams, and translating needs for product delivery. This role combines data leadership with client interaction and strategic planning.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.

Lead data platform strategy and architecture, scale Spark-based ETL/ELT pipelines, improve reliability and cost efficiency in an AWS environment, strengthen governance and lineage, modernize ingestion (Fivetran), and mentor engineers while delivering production-grade data solutions for analytics and AI.

Lead and oversee end-to-end polling operations: design and program surveys, construct samples, compute weights, analyze results, produce toplines/crosstabs, coordinate with data science, manage and mentor polling staff, and improve polling processes and vendor relationships to deliver client insights.

Manage and mentor a team of data scientists and engineers, guide development and delivery of ML/AI solutions, ensure best practices, collaborate with stakeholders, and align data science work with business objectives.

Design, build, and maintain production data pipelines and the unified data model using Snowflake, dbt, and orchestration tools. Optimize, test, document, and monitor ELT workflows, enforce engineering best practices, mentor teammates, and deliver trustworthy data products for analytics and business decisions.

Partner with Product leadership to build scalable Snowflake data models, run behavioral and funnel analyses, design A/B tests and predictive models, and translate insights to influence roadmap and product strategy.

Lead development of provider data products and ML-based decision support, manage provider data quality, collaborate across teams to build provider-facing analytics, and establish MLOps standards and governance.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

Lead the data organization to define data strategy, build scalable cloud-native pipelines, enable self-service analytics, drive AI/ML initiatives, and manage a multidisciplinary team to inform product, clinical, and business decisions.