Top Data & Analytics Jobs in Hartford, CT

Own data partner specification negotiations, data mapping, Ascend platform configuration, and internal QA across multiple implementations. Review file specifications, normalize schemas, validate test files, document data dictionaries, and route non-standard requests to Product or Customer Engineering. Coordinate with delivery and engagement teams on UAT, defects, readiness, and capacity constraints. Develop repeatable QA frameworks, implementation playbooks, procedures, and training materials while ensuring configurations meet quality standards before go-live.

Design, build, and own business-critical data infrastructure, including AWS Glue and Spark pipelines, cloud warehouse or lakehouse systems, orchestration, and Tableau BI platforms. Define event-driven contracts, data models, schemas, observability, and batch or streaming architectures across multi-tenant, multi-region environments. Collaborate across producer and consumer teams while owning production data infrastructure and outcomes end to end.

Lead a BI engineering team, overseeing dashboards, data models, SQL/dbt transformations, ETL pipelines, Airflow DAGs, data warehouses, CI/CD, governance, and quality standards. Partner with stakeholders to define reporting requirements, conduct advanced analyses, manage Agile projects, and develop data strategy. Mentor team members and support production deployments. This fully remote role requires travel to Denver for five business days each quarter.

The BI Engineer administers enterprise BI and analytics platforms, governs data consumption, and develops dashboards, reports, KPIs, and self-service analytics. The role translates business requirements into scalable, validated solutions; manages access controls, metadata, data quality, continuity planning, platform costs, and process improvements. It also provides stakeholder consultation, resolves complex technical issues, mentors teammates, and supports enterprise data transformation using Power BI, Tableau, Azure, SQL, and multiple database technologies.

Leads the architecture, design, and implementation of Azure-based analytics and data engineering solutions. Develops and optimizes data pipelines, ETL/ELT processes, query layers, Delta Lake solutions, and integrations across Databricks, Azure Data Lake, Synapse, Data Factory, and Power BI. Partners with stakeholders, oversees end-to-end delivery, ensures security and governance, documents data flows, and mentors data engineers while promoting scalable, high-quality solutions.

Analyze and model property catastrophe reinsurance treaties using catastrophe modeling platforms. Prepare and validate exposure data, execute models, interpret risk metrics, develop scenarios, and identify portfolio risk drivers. Support underwriting, actuarial pricing, placement, renewals, and management decisions through clear reporting. Participate in model validation, calibration, research, and development while collaborating with underwriters, actuaries, and other stakeholders.

Leads enterprise data strategy, governance, quality, reporting, and information systems for healthcare and PBM business units. Manages development and reporting teams, owns the data roadmap, serves as product owner, and partners with corporate and client IT teams. Oversees data platforms, AWS infrastructure, SQL databases, security assessments, compliance, issue resolution, and strategic data initiatives while promoting data-driven decision-making and standardized data practices.

Design and support ETL, data migration, transformation, import, export, and validation workflows for moving legacy EHR data into athenahealth systems. Build Python and SQL utilities, define source-to-target mappings, support HL7 and FHIR interoperability, validate EHI exports, investigate data quality issues, document processes, and collaborate with product, implementation, operations, sales, and engineering teams in a remote environment.

Leads a team delivering Customer Success reporting, dashboards, KPI frameworks, and operational analytics. Oversees reporting accuracy, data integrity, recurring metrics, workflow improvements, and automation. Partners with Customer Success and services leadership to translate business needs into analytical requirements, prioritize initiatives, standardize reporting methodologies, and communicate performance insights. Coaches analysts, manages workload and development, and supports data-driven operational decision-making and scaling.

Lead study design, survey development, questionnaire quality, data analysis, and client-ready reporting for financial services research. Interpret findings with client teams, translate results into actionable business insights, apply analytical methods, and ensure accuracy, clarity, timeliness, and integrity across multiple projects.