Top Remote Data & Analytics Jobs

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Join SignalFire's talent network to be considered for data engineering roles at VC-backed startups. Responsibilities include designing and maintaining batch and real-time pipelines, building data models and cloud data platforms, enabling analytics and ML pipelines, ensuring data quality/observability and governance, integrating varied data sources, improving performance and cost efficiency, and partnering cross-functionally to define data architecture and tooling.

Join a talent network connecting data engineers with VC-backed startups. Build scalable batch and real-time pipelines, data models, warehouses/lakehouses, ensure data quality, support ML pipelines, integrate diverse data sources, and define data architecture and governance.

Work with clients and technology teams to gather and translate business requirements into technical user stories and solutions, propose process improvements, and communicate effectively with stakeholders. Assist in analytical solution delivery and may write/execute SQL queries.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Support design, development, and maintenance of data pipelines and infrastructure. Assist with ETL/ELT workflows, data ingestion, cleaning, validation, modeling, and warehousing. Document processes and collaborate with data teams to support analytics use cases.

Design and govern end-to-end data architecture for an integrated supply-chain e-commerce platform: create data models, build scalable ETL/ELT pipelines, ensure GDPR-compliant data governance, enable real-time analytics, optimize databases, plan retention/archival, and prepare data for LLM fine-tuning and RAG use cases.

Senior Data Architect contractor to accelerate and modernize the data platform: assess landscape, design end-to-end data solutions, define integration and metadata patterns, enable data mesh and cloud migration (AWS), and produce reusable architecture artifacts for handoff to engineering teams.

Lead digital measurement analytics for servicing platforms: design/validate data collection, build reporting and feature measurement, collaborate with stakeholders, mentor team members, and drive analytics roadmap and actionable insights.

Lead design, development, automation, and maintenance of BI products for Health & Wellness. Build dashboards, datasets, semantic layers, and standardized reports using SQL and SAS, partner with stakeholders to translate requirements, ensure performance and governance, optimize BI solutions, document definitions, and train teams while supporting cloud/AI initiatives.

Lead design, development, automation and maintenance of BI products (dashboards, datasets, semantic layers). Translate stakeholder requirements into governed, performant BI solutions using SQL, SAS and BI tools; optimize performance, document metrics, apply access controls, and train teams to drive adoption and measurable business outcomes.

Organise and curate large amounts of raw material: extract key points from transcripts, collate and maintain clean spreadsheets, tag and categorise links and documents, and create findable information structures following or suggesting systems.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.