Top Data & Analytics Jobs

Owns data systems workstreams for public fixed income investment operations. Leads process improvement and automation, develops reports, dashboards, and data models, manages data quality and issue resolution, and performs portfolio analysis, forecasting, benchmarking, and financial modeling. Partners with investment, client, and business teams on reporting and analytics while supporting technology implementations, translating business needs into technical requirements, and mentoring junior analysts.

Performs data profiling, validation, quality testing, anomaly detection, pipeline monitoring, and quality reporting across cloud and on-premises environments. Builds validation rules and data quality artifacts, collaborates with business and technology stakeholders, leads solution design and estimation, and mentors Data Quality Analysts. Works with data lakes, data warehouses, datamarts, and enterprise data platforms.

The Data Analyst develops production-grade data and analytics solutions by translating business needs into functional requirements, analyzing and validating data, and contributing to architecture, governance, modeling, quality, engineering, and data science initiatives. The role independently leads solution design and estimation, collaborates with business and technology stakeholders, mentors analysts, and applies SQL, big data, cloud, and data storage expertise to solve complex business problems.

Build and maintain cloud or on-premises ETL/ELT pipelines for large-scale structured and unstructured data processing. Ensure data quality, security, and compliance while collaborating with business, technology, operations, governance, architecture, data science, DevOps, and BI teams. The role requires expertise in big data frameworks, Azure services, distributed databases, data warehouses, data marts, and data lakes.

Leads the design, development, and maintenance of scalable batch and real-time data pipelines across Azure and on-premises environments. Builds production-grade ETL/ELT solutions, optimizes performance and reliability, ensures data quality and compliance, and solves complex business problems. Collaborates with business and technology stakeholders, leads solution design and estimation, and coaches data and analytics talent.

Leads enterprise data and analytics strategy, architecture, modernization, and delivery across cloud and on-premises environments. Oversees data platforms, engineering, integration, governance, quality, lineage, security, and compliance. Partners with executives to define roadmaps and investments, manages cross-functional teams and vendors, enables AI/ML capabilities, and mentors data professionals while driving scalable, trusted data solutions and measurable business outcomes.

Develops and maintains Access databases, SQL reports, Cognos and Power BI dashboards, SharePoint solutions, and operational workflows. Analyzes transactional, financial, staffing, productivity, and performance metrics; validates data; creates projections and regulatory reports; and presents findings to senior leadership. Partners with stakeholders and IT to gather requirements, improve processes, automate workflows, ensure data integrity, and support compliance and business operations.

Undergraduate interns will support data and analytics projects involving data pipelines, machine learning, generative AI, dashboards, reporting, data governance, process improvement, production support, and analytics solution development. Interns will collaborate cross-functionally, document data assets, validate data, and present project outcomes. The hybrid program requires approximately 40 hours weekly for ten weeks in Cary, North Carolina.

Analyze reinsurance data and business processes, gather requirements, create data mappings and flow diagrams, and support FAIRR Data Hub solutions. The role validates data quality, governance, reconciliation, and technical specifications while partnering with business, technology, architecture, engineering, and governance teams. It also contributes to reporting, AI-enabled analytics, solution testing, stakeholder communication, and mentoring junior analysts.

Develop, test, deploy, and support Azure-based ETL/ELT data pipelines using SQL, Python, or PySpark. Perform data ingestion, transformation, validation, modeling, quality checks, documentation, monitoring, and incident support. Apply security, privacy, lineage, retention, and regulatory controls to sensitive insurance data. Collaborate with engineers, analysts, application teams, security, and governance stakeholders in a multinational agile environment.