Top Remote Data & Analytics Jobs in Hartford, CT

Supports federal market intelligence, capture, and proposal activities through procurement research, opportunity and competitor tracking, data maintenance, and basic quantitative and qualitative analysis. Maintains intelligence databases, trackers, dashboards, and reports using federal procurement platforms and Excel. Coordinates research requests with business development and capture teams, prepares briefs and summaries, and independently handles smaller assignments. Requires experience in small-business federal contracting, including SBA 8(a) and set-aside programs.

Leads complex, enterprise-scale data engineering initiatives using Databricks and Azure. Designs and implements scalable lakehouse architectures, high-performance pipelines, and platform capabilities while establishing engineering standards for reliability, security, observability, and cost efficiency. Mentors engineers, leads through influence, embeds across teams to accelerate delivery, manages technical risks, and advises stakeholders on data strategies and architectural trade-offs. Collaborates with Architecture, Platform, AI, Analytics, Security, and Governance teams.

Develops business intelligence, reporting, data pipelines, dashboards, and geospatial solutions for complex real estate portfolios. Transforms and integrates data from multiple sources, builds scalable analytics products, automates reporting processes, and supports portfolio planning, occupancy strategy, workplace initiatives, and operational decision-making. Partners with stakeholders and clients to translate business needs into technical solutions, communicate insights, train users, and improve analytics adoption. The role also supports geospatial capabilities and leverages emerging AI-enabled tools.

The Data Engineer designs, builds, and optimizes enterprise data pipelines, lakes, warehouses, integrations, and analytics infrastructure. Responsibilities include ELT development using Snowflake and Informatica, data governance, quality, security, performance monitoring, PII protection, cost optimization, and support for analysts and data scientists. The role also delivers process improvements, analytics tools, stakeholder collaboration, technical mentoring, and scalable data architecture across cross-functional teams.

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.

Leads the strategy, architecture, and execution of an enterprise data platform supporting analytics, machine learning, operational systems, and AI applications. Manages and mentors data platform engineers while remaining hands-on with architecture, reliability, technical direction, and troubleshooting. Oversees pipelines, orchestration, governance, security, observability, data contracts, migrations, and platform operations. Partners cross-functionally to translate business needs into scalable technical solutions and communicates decisions to technical and non-technical stakeholders.

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.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, experiments, and analyses; surface insights; make recommendations; and drive decisions and execution with cross-functional stakeholders. The role requires independently structuring ambiguous problems, interpreting data, communicating persuasively with leadership, and delivering measurable business impact.

Own the end-to-end analytics function embedded in a business unit (growth, product, AI/automation, or partnerships). Define problems and metrics, build reports and experiments, surface insights, recommend actions, and drive outcomes with cross-functional partners.

Lead enterprise data analytics, pipelines, BI, and data governance. Build and monitor ELT/ETL pipelines, develop executive dashboards, define data contracts and domain models, standardize integration patterns, and ensure HIPAA/SOC2-compliant data practices across affiliated entities.

Provide MEAL technical advice and capacity strengthening to country teams and partners across RAPID and EMPOWER projects. Support MEAL system design and implementation, digital data-collection tools (Kobo/CommCare), data management, analysis, visualization, feedback and complaints systems, proposal MEAL components, and documentation. Conduct trainings, capture lessons learned, and represent CRS with donors and partners to improve program quality and accountability.

The ClaimsXM Data Engineer III role has limited responsibilities listed. The position requires U.S. citizenship or naturalized citizenship and requires all work to be completed within the continental United States, Alaska, or Hawaii.