Top Remote Data & Analytics Jobs in Washington, DC

Process, validate and QA large survey datasets; produce datasets, tables, codeframes and documentation; support weighting, testing and statistical analyses; learn and apply Python/R, automation and AI-assisted tools; improve automated processing workflows under senior guidance.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Own and build customer health, usage/adoption, and product configuration data models. Produce ad-hoc and recurring analyses to identify upsell/expansion opportunities, partner with CS, Sales, Product, and Data teams, and present actionable insights to leadership to drive revenue-relevant actions.

Build and support high-performance data solutions, design and operate ETL pipelines and data warehouses, monitor production analytics tools, troubleshoot system issues, collaborate with product teams, and support TechOps for analytics infrastructure.

Design and own data migration strategy and architecture. Map source-to-target data models, build data dictionaries, perform migrations and testing, reconcile results, and collaborate with stakeholders and project teams to ensure successful modernization.

Design and build complex dashboards and interactive visualizations in Power BI and SAP SAC; integrate and model data from SAP BW, SAP HANA, and SQL; develop planning models and advanced formulas for financial/operational planning; gather requirements from stakeholders; optimize dashboard performance, manage data pipelines, and maintain report stability.

Architect and scale a governed BI and analytics platform (Snowflake, dbt, Sigma) to deliver trusted, standardized KPI frameworks and semantic layers. Build high-quality data models, optimize SQL for large datasets, enable self-serve analytics, mentor engineers, drive governance and testing standards, and partner with Product, Data Science, Finance, and business teams. Promote AI-assisted tooling to accelerate analytics delivery and improve metric trust and reporting consistency.

Own and build the support reporting layer: ticket volume, SLA, resolution times, CSAT/CES/sentiment, and capacity. Produce dashboards and analyses for leadership and engineering, maintain data quality and governance, prioritize issues using multi-signal models, and surface Voice of Customer trends to close the loop with Product and GTM.

Join Kled to help build the future of human data collection and design systems that influence AI data training through a consumer application.

Design and build cloud-based data applications and pipelines to analyze clinical data, enrich and provision datasets, and support clinical/operational processes. Mentor junior engineers, drive R&D for repeatable templates, collaborate with Product/Platform/Architecture, and prioritize source control, documentation, and simple solutions using modern data, ETL, and LLM tooling.