Top Data & Analytics Jobs

Support business technology by developing Power BI dashboards, low-code Power Apps/Power Automate solutions, validating and analyzing data with SQL, improving data governance, participating in SDLC, providing user support and training, and automating business processes to increase efficiency and data accuracy.

Leads the design, development, governance, and operational support of enterprise data engineering solutions for Fresh Meats analytics. Builds cloud-based data lakes, pipelines, models, integrations, and reporting-ready datasets; implements security, data quality, lineage, observability, and governance controls; supports production incidents and releases; and partners with business, platform, and governance teams. Mentors engineers and analysts while ensuring scalable, documented, secure, and reliable data products.

Lead the development, refinement, validation, and communication of commercial real estate econometric forecasting models. Monitor forecast accuracy, conduct quantitative research, develop new models, improve data and methodologies, document processes, create dashboard inputs, and educate internal teams and customers on forecast results and model validation.

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.