Top Data & Analytics Jobs

Serve as the technical/business liaison between Finance & Accounting and IT: gather and document requirements, map data flows, support finance transformation projects, produce process and test artifacts, troubleshoot production issues, and facilitate design sessions to deliver analytics, reporting, and automation solutions for financial reporting and operations.

Lead product strategy, roadmap, and delivery for commercial BI products. Partner with cross-functional stakeholders to build scalable dashboards, KPI frameworks, and reporting; manage backlogs and releases; ensure governance, data quality, and adoption; recommend BI/AI technologies and drive continuous improvement.

Lead feature delivery for Oracle-centric data pipelines and analytics platforms. Design, implement, and optimize PL/SQL packages, procedures, and ETL; automate jobs with Autosys and Unix shell scripting; perform data modeling, profiling, and performance tuning; mentor developers, support testing/UAT, and collaborate with stakeholders to ensure compliant, stable, high-quality database solutions.

Design, build, test, and support scalable data pipelines and reporting solutions for AML. Integrate, transform, and validate data, monitor production systems, troubleshoot issues, and collaborate with product, engineering, and business teams to ensure data quality, performance, and regulatory compliance.

Lead workforce analytics function advising HR and business leaders; develop predictive and diagnostic analyses for retention, recruiting, mobility, and workforce planning; supervise consultants, set analytics standards, prioritize projects, deliver executive presentations, and build analyst capabilities.

Support Finance modernization by translating stakeholder needs into BI and automation solutions. Develop and maintain analytics, reports, and low-complexity automations; ensure data quality; support UAT and deployments; provide post-deployment support, documentation, and training; and apply continuous improvement practices to Finance processes.

Manage day-to-day BI reporting and Microsoft Fabric/Lakehouse operations; lead a small BI team; build and maintain Power BI reports, semantic models, pipelines, and access controls; prioritize and deliver requests across Finance, Operations, Manufacturing, Inventory, Sales, and Projects while ensuring KPI consistency, performance, and documentation.

Lead and grow a data engineering team to design, build, and operate scalable, cost-efficient data lakehouse pipelines and infrastructure. Define technical strategy, enforce engineering best practices (CI/CD, testing, monitoring), own roadmap and capacity planning, collaborate with product and engineering stakeholders, manage on-call and operational automation, and hire talent. Ensure data governance, lineage, and compliance in a regulated healthcare environment.

Lead design and implementation of data ingestion, data lake, and ETL solutions using Big Data technologies. Build performant cloud data pipelines, integrate multiple data sources, optimize query performance, enable analytics and data science teams, and lead offshore engineering teams.

Design, deploy, and administer Hadoop/Big Data platforms. Install, upgrade, patch, configure, and support Hadoop ecosystem components. Manage HDFS security and ACLs, backup and disaster recovery. Work with business teams to gather requirements, write technical documentation, and manage priorities and operational support.

Design, architect, and implement scalable high-performance big data solutions on Hadoop ecosystems. Lead workshops, produce proposals and technical documentation, perform reviews, profiling, troubleshooting, cluster sizing, and deploy clustered solutions. Mentor senior leaders and contribute to open-source integrations.

Lead Tableau architect responsible for designing and deploying enterprise dashboards and rich visualizations (drill-downs, parameters). Build dashboards using calculations, sets, groups, and advanced reporting objects. Strong SQL and dimensional/relational data modeling skills required.

Lead analytics to measure and improve end-to-end client experience. Own sentiment and performance analysis (NPS, CSAT, churn, health), design measurement frameworks and leading indicators, build executive dashboards, perform root-cause and financial impact analyses, partner cross-functionally to optimize journeys, and convert qualitative and quantitative insights into prioritized actions.