Top Remote Data & Analytics Jobs

Develop and optimize large-scale data systems, ETL pipelines, storage, entity-resolution products, and data automation infrastructure. Build and integrate ingestion and processing pipelines using AWS, Airflow, Spark, PySpark, and EMR. Create testing and monitoring components, develop analytical tools, support data governance and quality, collaborate with data science teams, and document technical solutions.

Own and evolve end-to-end data pipeline architecture across ingestion, transformation, modeling, and serving. Lead platform improvements for cost efficiency, reliability, access control, observability, orchestration, CI/CD, and developer experience. Drive complex cross-team initiatives, resolve production issues, influence architectural decisions, mentor engineers, and build automation incorporating AI into data engineering workflows.

Own pharmaceutical media performance reporting, analyze marketing data, develop dashboards, identify optimization opportunities, and present actionable insights to clients. Support attribution, test and control analyses, predictive modeling, AI-enhanced reporting, and process improvements. Collaborate with strategy, analytics, media, client services, data science, and technology teams to advance reporting capabilities and data-driven decision-making.

Manage a team of 2–3 analysts while remaining hands-on with SQL, dbt models, dashboards, and complex operational analyses. Lead ambiguous, cross-functional initiatives, deliver recommendations to senior stakeholders, ensure data quality, and improve reporting automation. Partner on AI analytics strategy, data readiness, agent evaluation, and human-in-the-loop governance. Responsibilities include coaching, prioritization, performance management, technical review, KPI development, and operational insights across customer experience, fraud, payments, workforce management, and VIP functions.

Own the analytics roadmap, data platform, semantic models, customer-facing analytics, and AI-native analytics agents. Partner with cross-functional leaders to establish trusted metrics, improve operational and patient-access insights, and deliver data products that drive measurable outcomes. Strengthen dbt and Snowflake foundations, create governed self-service workflows, and provide technical mentorship as the analytics function grows.

Organize and curate large volumes of raw information: extract key points from transcripts, maintain clean spreadsheets, curate links/resources, tag and categorize content, and follow or propose systems for information structure. Part-time remote role with initial 10 hours/week and potential to grow.

Leads advanced business analytics across Commercial, Finance, and Operations. Builds scalable solutions using SQL, Python, Snowflake, Tableau, and Power BI; performs forecasting, statistical analysis, segmentation, predictive modeling, and exploratory analysis. Develops semantic models, KPI frameworks, data governance practices, and reusable datasets while improving data quality and pipelines. Partners with leadership and technical teams to translate complex data into actionable insights, automate decision support, and influence strategic business outcomes.

Build and operate production pipelines for legal records from PACER, court systems, opinions, PDFs, scans, XML, and HTML. Develop LLM-assisted extraction workflows, validate data quality, optimize SQL, and support RAG and semantic search products. Manage AWS S3 and RDS systems within security guardrails while collaborating with engineering teams. The role requires strong Python and SQL skills, legal data experience, document extraction expertise, and autonomous problem-solving with large, messy datasets.

Designs and maintains Power BI reports and dashboards using Microsoft Fabric semantic models. Builds data models, writes and optimizes DAX, applies security controls, validates data quality, and creates certified datasets and reusable templates. Partners with stakeholders to define reporting requirements, presents insights, participates in peer reviews, and uses AI tools to improve analysis and delivery.

Leads analytics and data engineering for Sales and Revenue Operations. Builds reporting in Looker and Snowflake, manages CRM data flows into cloud warehouses, establishes transformation and modeling layers, and develops forecasts, scoring, churn, and expansion models. Supports territory, quota, pricing, and revenue-truth initiatives while presenting insights to finance and company leadership.