Top Remote Data Management Jobs

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

Lead Compliance Data Analytics to research and analyze risk patterns (fraud, account takeover, payment fraud), deploy and iterate rules/models, partner with stakeholders to balance user experience and risk mitigation, drive business-centric analytics and strategic metrics, and build and manage a high-performing compliance analytics team.

Support partners in voter engagement by administering VAN and related tools, managing users/security, producing data pulls and visualizations, training partners on data hygiene and field tools, providing technical assistance, and coordinating with national and state data teams to maintain shared infrastructure and best practices.

Manage and grow a data engineering team, overseeing the design and maintenance of data platforms using Snowflake, dbt, and Azure. Drive best practices in data management and ensure reliable data movement and quality.

The Exposure Data Manager leads analytics to understand exposure patterns, enforces data standards, ensures data quality, and collaborates across departments for effective exposure management.

Manage delivery of complex data pipelines in a hands-on role, leading a team of data engineers to develop scalable data solutions and improve analytics capabilities.

The Data Product Manager will lead cross-functional teams to create high-impact data products, translate business needs into technical requirements, and manage product roadmaps. Responsibilities include collaborating with stakeholders, optimizing product performance, and ensuring compliance with industry standards.

Lead data engineering initiatives to build ingestion, integration, and common data models; enable data products and governance across domains; design scalable cloud-based data architectures and ML pipelines; collaborate with business and tech teams to deliver data products, ensure data quality, and drive adoption.

Lead a small data engineering team while contributing hands-on to design, build, and maintain production data pipelines, warehouse, ETL, and BI stack. Own data reliability, governance, reporting (internal and actuarial), enable self-service analytics, consolidate analytics standards, and drive infrastructure/vendor decisions aligned to business goals.

Own developer relations for GPU-accelerated analytical data processing: integrate NVIDIA libraries into query engines and OLAP databases, produce rigorous benchmarks, create reference integrations and guides, collaborate with engine architects and NVIDIA product teams to define APIs and roadmap, and drive adoption across open source and commercial projects.

The Clinical Data Manager oversees the quality and integrity of clinical trial data, ensuring compliance with protocols and regulations while collaborating with various teams.

The role involves leading the data governance team, managing IT projects, collaborating with stakeholders, and ensuring continuous improvement of processes. Responsibilities include strategic planning, client management, and optimizing resource utilization, while overseeing governance activities and departmental management.

Lead data management and quality for programs serving people experiencing homelessness. Supervise data coordinators, manage HMIS and other databases, conduct audits, ensure contract compliance and HIPAA adherence, produce reports for funders and leadership, provide training and technical assistance, and translate data into actionable recommendations.

The Data Product Manager defines the reporting roadmap, manages KPI alignment, collaborates cross-functionally, ensures data quality, and leads continuous improvement in analytics processes.

Lead and grow a data engineering team to build a trusted, fast, composable, and self-serve data platform. Define architecture and roadmap for ingestion, transformation, governance, and analytics; ensure reliability, observability, and security; partner cross-functionally with Product, Analytics, Security, and Engineering; be a hands-on player-coach delivering scalable data systems using Snowflake, dbt, and self-serve analytics.

Lead design, build, and operation of data architecture, pipelines, and semantic layers. Manage sprint planning, DevOps metrics, data quality and monitoring, and MLOps enablement. Partner with stakeholders, coach engineers, track project plans, and ensure data availability, accuracy, and documentation.

Lead and grow a data engineering team; define architecture and standards for ETL/ELT pipelines; hands-on design, code review, and development; ensure production reliability, monitoring, and incident response; partner with product and engineering on data roadmap.

Manage receipt-based data ingestion (OCR, transcription, email, account connections); ensure pipeline stability and data quality; translate business requirements into collection specs; partner with Engineering and Product; manage vendors, forecasting and budgets; produce KPI reporting; and support EU rollout and GDPR-aligned processes.

Lead and manage a remote Data Engineering team to build scalable data pipelines and lakehouse solutions. Own execution of Medallion architecture using Databricks, Boomi/Rivery, dbt, Delta Lake and SQL Server; implement DataOps, CI/CD, observability, and stakeholder intake while growing engineers and improving team maturity.

Lead a remote US team that builds and operates ETL and migration processes to move legacy EHR data into athenahealth. Oversee Python-based tooling, define source-to-target mappings, ensure HL7/FHIR interoperability and EHI export compliance, drive data quality, automation, documentation, stakeholder alignment, and coach engineers.

Lead and scale the enterprise data hub: manage the data warehouse, build reliable ingestion and transformation pipelines, implement governance and data modeling best practices, deliver GTM-ready metrics, enable AI/ML use cases, prioritize the data roadmap, and lead/mentor a data engineering team.

Lead enterprise data and analytics governance for a federal technology services program, ensuring secure and effective data usage and decision-making support.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

Lead combined Analytics Engineering and Data Engineering teams owning the end-to-end data roadmap from ingestion to trusted metrics. Manage hiring and performance, set architecture and platform investments, enforce testing/monitoring/documentation standards, review technical decisions, and partner with product and business stakeholders to translate needs into prioritized deliverables.

Lead and scale a distributed data engineering organization: design and maintain cloud-native data infrastructure, build ETL/ELT pipelines and event streams, ensure data quality and observability, deliver dashboards and analytics tools, partner with product and business stakeholders, and manage analytics project prioritization and team performance.