Top Data & Analytics Jobs

Hands-on principal data engineer defining enterprise-scale data architecture, building and optimizing data pipelines/integrations for analytics and ML, deploying production code, mentoring engineers, and partnering with product and ML teams to transform and analyze data for actionable insights.

Defines and governs enterprise data architecture across operational, analytical, AI/ML, and reporting platforms. Leads cloud data platform strategy, governance, modernization, security, DataOps/MLOps, architecture standards, and vendor evaluations. Partners with business, engineering, cybersecurity, risk, compliance, and executive stakeholders to deliver scalable, compliant, observable, and AI-ready data capabilities supporting insurance functions such as underwriting, claims, finance, and regulatory reporting.

Design, implement, and optimize large-scale data processing on Databricks and Spark. Build ETL pipelines, integrate data across AWS services (Redshift, RDS), orchestrate workflows with Airflow, and ensure data warehousing and engineering best practices. Lead and mentor development teams and collaborate with cross-functional stakeholders to drive data strategy and execution.

Develops and maintains Power BI dashboards, reports, and analytics solutions for manufacturing operations. Analyzes operational data to identify trends and support factory decision-making, integrates machine-level data into fairlife’s Unified Factory Data Model, validates data quality, upholds governance and reporting standards, and trains end users on BI tools and data literacy.

Owns business intelligence and data management for investment operations, developing Power BI dashboards, DAX and Power Query models, Snowflake reporting data, and secure data access. Leads strategic business initiatives, workflow improvements, technology enhancements, AI and LLM automation, stakeholder reporting, vendor coordination, requirements gathering, and project execution. Serves as the subject matter expert for data, reporting, client portals, metrics, and internal technology initiatives.

Develops and delivers operational and analytical data solutions within an enterprise data warehouse and business intelligence environment. Responsibilities include building data pipelines, creating logical data models and mappings, supporting requirements through implementation, testing and maintenance, partnering with analysts and IT teams, and investigating data quality issues. The role requires experience with programming, cloud platforms, data warehouses, databases, ETL tools, and Windows/Linux systems.

Develop and maintain business intelligence solutions, including data models, reports, queries, dashboards, datasets, and transformations. Extract and integrate data from SAP and PeopleSoft Campus Solutions, analyze business processes and source systems, and translate stakeholder needs into reporting solutions. Responsibilities include solution design, testing, troubleshooting, documentation, data governance, performance optimization, and support for institutional financial, student, operational, and strategic reporting.

Develops and maintains healthcare data integration and EDI solutions, including ETL processes, data pipelines, data validation, cleansing, transformation, reporting, and compliance testing. Troubleshoots applications, manages code reviews, documents systems, and collaborates with analysts, healthcare providers, business partners, and IT teams. The role also implements security measures and recommends improvements to integration processes.

Provides executive leadership for advancement analytics, business intelligence, reporting, data governance, integrations, data architecture, AI enablement, innovation, and organizational learning. Establishes data strategy and governance, oversees analytics and decision-support capabilities, leads directors and analysts, and partners with university stakeholders to improve fundraising effectiveness and organizational performance.

Architect and maintain NetBrain’s first cloud data warehouse, ELT pipelines, transformation layer, semantic models, and BI foundation. Own data quality, governance, lineage, access controls, and curated models supporting product usage, customer adoption, account health, and go-to-market reporting. Partner with stakeholders to establish reliable metrics and a standardized source of truth, while supporting AI-assisted analytics and natural-language reporting use cases.