Top Data & Analytics Jobs

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.

Designs and maintains healthcare data pipelines, ETL workflows, databases, data models, and analytical frameworks. Analyzes claims and payer data to identify trends and insights, while ensuring data quality and integrity. Creates reports, dashboards, and visualizations for nontechnical stakeholders and collaborates with healthcare policy experts, analysts, and other stakeholders to translate requirements into data solutions. The role also improves data infrastructure and analytics capabilities.

Analyze complex datasets to identify trends, patterns, anomalies, and business opportunities. Develop KPIs, perform root-cause analysis, build Power BI dashboards using DAX, SQL, and Power Query, validate data quality, automate reporting, and translate findings into actionable recommendations for business stakeholders.

Conduct online research, gather and verify information from multiple sources, evaluate source reliability, and prepare structured notes, summaries, and reports. Identify organizations, professionals, publications, and industry data while maintaining accurate source records. The role requires clear written English, strong attention to detail, analytical thinking, consistent documentation, and independent time management.

Own the data and insights portfolio for Gainbridge, prioritizing business problems that analytics and AI can solve. Translate data and models into decisions, drive adoption within workflows, build data literacy, and govern applied AI use. Partner with data and engineering teams on use cases while retaining accountability for business outcomes, prioritization, acceptance, and stakeholder alignment.

Designs and maintains scalable data pipelines, ETL/ELT workflows, data models, data lakes, warehouses, and curated data layers. Integrates structured and unstructured data from internal systems, vendors, and APIs, while supporting Tableau dashboards and analytics. Monitors pipeline reliability, performance, governance, validation, security, and data quality. Collaborates with analysts, data scientists, developers, and stakeholders to deliver cloud-based data solutions, documentation, and AI-enabled analytics capabilities.

Design, build, and operate scalable batch and near-real-time data pipelines on AWS. Lead complex data engineering projects, translate business needs into data models and technical solutions, ensure data quality and reliability, and shape platform roadmaps. Integrate AI workflows such as LLM orchestration, embeddings, and vector search while collaborating with product and engineering teams across financial and analytical products.

Develops business cases, financial and operational models, data models, executive decision packages, portfolio dashboards, and benefit-validation reporting for cross-functional transformation initiatives. Extracts and analyzes enterprise data using SQL, Python, spreadsheets, and visualization platforms; automates repeatable workflows; standardizes metrics; tracks value realization; and partners with Finance, IT, data engineering, and business leaders to support decisions and embed sustainable reporting processes.

Manage and validate large datasets across investment operations, including daily and monthly cash and position reconciliations, security and pricing data maintenance, data pipelines, and ETL processes. Support compliance monitoring, resolve discrepancies, improve operational workflows, and collaborate with custodians, clients, counterparties, vendors, and internal teams. The role requires strong analytical skills, attention to detail, Excel expertise, and experience in investment operations or financial services.

Leads the analytics function, establishes trusted KPIs and self-service reporting, and translates customer, operational, and financial data into executive recommendations. Oversees Looker reporting, data quality, analytics strategy, predictive use cases, profitability analysis, planning models, and cross-functional resource allocation. Coaches analytics staff and partners with Data Engineering and business leaders to identify growth opportunities, risks, and operational improvements.