Top Data & Analytics Jobs

Performs institutional data analysis, statistical reporting, program assessment, and research to support university planning and accountability. Develops and maintains statistical programs, data archives, web-based collection and reporting mechanisms, and administrative report-writing tools. Conducts quantitative and qualitative analyses, prepares institutional studies, supports strategic planning and enrollment management, and communicates findings to faculty and staff while maintaining data integrity and confidentiality.

Transforms operational telemetry, incident, change, event, observability, and service management data into actionable insights. Develops dashboards, scorecards, KPIs, reliability metrics, and executive reports; identifies operational risks and improvement opportunities; supports incident, problem, change, reliability, and production operations teams; and improves data integration, automation, alert correlation, and predictive operational analytics.

Designs, builds, and operates reliable Azure data pipelines using Databricks, Azure Data Factory, PySpark, Spark SQL, and Delta Lake. Responsibilities include batch and streaming ingestion, ELT transformation, dimensional modeling, data quality enforcement, CDC, schema management, monitoring, alerting, governance, CI/CD, documentation, and operational support. Partners with architects, BI developers, and stakeholders to deliver analytics-ready datasets and improve pipeline performance, reliability, and cost efficiency.

Analyzes complex healthcare data to identify trends, develop statistical and machine learning methodologies, and produce actionable insights. Builds dashboards and reports, supports product and business decisions, promotes data literacy, and collaborates with cross-functional teams. The role also ensures analytics practices comply with healthcare privacy, governance, security, and regulatory requirements, including HIPAA.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Design and evolve enterprise data architecture, scalable data models, integration patterns, governance, lineage, quality, cataloging, and MDM solutions. Modernize data platforms and enable AI and advanced analytics while providing architectural leadership to data and engineering teams. The role partners with business and technical stakeholders to align data strategy with operational needs, evaluate technologies, and establish enterprise standards.

Leads enterprise data and AI strategy, governance, stewardship, shared data platforms, and responsible AI enablement in a federated operating model. Partners with executives, architecture, cybersecurity, audit, compliance, and business domains to ensure trusted, secure, scalable data capabilities. Builds and develops teams across data governance, engineering, analytics, and AI while driving enterprise alignment, platform adoption, data quality, and measurable business value.

Supports and enhances enterprise data systems, databases, integrations, and analytics platforms. Responsibilities include SQL development, database administration, performance tuning, production troubleshooting, backup and recovery, data pipeline development, Microsoft Fabric support, Power BI reporting, data modeling, security, governance, and documentation. The role collaborates with application developers, infrastructure teams, analysts, business stakeholders, and vendors to deliver reliable, scalable enterprise data solutions.

Build and maintain large-scale AWS ETL and data-processing pipelines handling billions of records. Investigate data-quality issues, analyze scoring outcomes, optimize query and processing performance, integrate diverse data sources, and develop reliable datasets. Own architecture and projects end to end, including testing, validation, production troubleshooting, and documentation. Apply statistical, machine-learning, AI, and analytical methods to improve data accuracy, scalability, and product outcomes with limited oversight.

Builds and maintains global Workday HR reporting infrastructure: gathers requirements, develops custom reports and dashboards, tests and validates solutions, supports UAT, mentors peers, handles ad-hoc data requests, and improves report performance and user adoption across HR teams.