Top Remote Data & Analytics Jobs

Supports consulting projects involving business intelligence system analysis, design, implementation, dashboard creation, data collection, dataset organization, data management, and business analysis. Interns use visualization tools to communicate insights, assist with client technology and process-improvement initiatives, and participate in training while collaborating with senior mentors and client teams.

Build and maintain ETL/ELT pipelines to move product data into analytics-ready stores (Postgres, data lake, warehouse). Design and optimize data models, ensure data quality and documentation, support ad-hoc research requests, and collaborate with research and engineering teams to enable reproducible analytics.

Supports portfolio planning and operational analytics for auto insurance program delivery. Analyzes capacity, forecasts, rollout sequencing, dependencies, and performance metrics; builds dashboards, schedules, and reporting tools; conducts scenario analysis; and recommends delivery trade-offs. Partners cross-functionally with program management, state management, data science, and technology teams to maintain realistic roadmaps and improve planning workflows using Power BI, Power Apps, JIRA, Excel, AI, and automation.

Build and operate production data pipelines and dimensional models using Spark, SparkSQL, and cloud lakehouse technologies. Own pipelines from requirements through deployment, monitoring, and iteration; improve data quality, lineage, reliability, and cost efficiency. Partner with data scientists, analysts, product managers, and engineers to support datamarts, KPIs, reporting, and analysis. Participate in business-hours on-call rotations and improve runbooks and alerting.

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.

Prepares annual Medicare Advantage Part D bids, analyzes healthcare costs and trends, develops pricing and forecasting models, and produces reports for CMS submissions and leadership decisions. Builds AI-powered solutions and data pipelines using Python, SQL, and related tools to improve efficiency. Requires healthcare insurance and pharmacy claims experience, advanced Excel proficiency, and strong analytical, modeling, and prioritization skills.

Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred.

Develop and maintain secure, scalable data pipelines and production code using AWS, PySpark, Python, and ETL technologies. Extract and transform data, implement quality checks, optimize data processing workflows, support cloud data modernization, and ensure reliable data availability. Collaborate with cross-functional teams, troubleshoot technical issues, automate recurring remediation, and communicate with technical and non-technical stakeholders. The role also involves software testing, operational stability, continuous delivery, and potentially mentoring other engineers.

Own and operate Toast’s enterprise data governance program, including data domain ownership, governance council coordination, policy compliance, business glossary management, metadata standards, catalog adoption, maturity assessments, and data literacy training. The role partners with business stakeholders, data stewards, catalog teams, and leadership to improve data trust, compliance, discoverability, and quality. It requires governance, metadata, SQL, data catalog, program management, and workshop facilitation experience.

Owns analytics and optimization strategy for advertising revenue across Zynga’s mobile game portfolio. Responsibilities include monitoring performance, diagnosing trends, designing A/B tests, identifying monetization opportunities, partnering with product, analytics, and data science teams, supporting AI and ML models, leading cross-functional initiatives, and mentoring analysts.