Top Data & Analytics Jobs

Design, build, and operate enterprise-scale Microsoft Fabric data platform components and semantic models. Engineer scalable ELT pipelines, tune Spark/Delta workloads, enable secure governed data products, improve platform reliability and observability, and accelerate AI-native engineering with agentic workflows to support analytics, automation, and AI at scale.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Design and deliver executive-ready Power BI reports, dashboards and agentic experiences. Build semantic models and self-service analytics, apply DAX, Power Query and Fabric notebooks, perform data exploration with SQL/KQL, and drive AI-enabled automation. Collaborate with data engineering to influence ingestion and transformation, translate business strategy into data solutions, and ensure performance, reliability, and scalability of reporting assets.

Develop and manage executive-facing dashboards and financial reports, maintain P&L data infrastructure and daily ingestion, ensure audit-ready accuracy, partner with business leaders to drive competitive strategy and analytics improvements.

Lead institutional intelligence, analytics, and performance management to support strategic planning and decision-making. Manage dashboards, KPI tracking, data governance, program reviews, and analytic reporting. Provide actionable insights, monitor strategic initiatives, and coordinate performance review cycles to advance college priorities and organizational effectiveness.

Design, build, and maintain scalable distributed data pipelines and a secure data lakehouse for streaming and batch processing to support real-time analytics, ML, and experimentation. Automate, test, and harden workflows, architect logical and physical data models, build ML model features, and collaborate with product, analytics, and data science teams to turn data into value.

Design, build, and maintain scalable dbt transformation pipelines and dimensional data models on Databricks. Partner with data engineering and stakeholders to deliver trusted silver/gold datasets, implement data quality tests and monitoring, enable self-service semantic layers, and enhance LLM-driven tooling to accelerate analytics and automation.

Design, build, and maintain large-scale data pipelines, ETL/ELT processes, and data models. Collaborate with analysts, architects, and data scientists to deliver BI solutions, optimize performance, support production systems, and mentor team members. Implement cloud and on-prem data architectures, CI/CD practices, and tooling to enable data-driven decision-making across the business.

Design, build, and maintain data pipelines, ETL/ELT processes, and data warehouses. Develop complex data models, tune SQL/PLSQL, support production BI/reporting, and collaborate with analysts and architects to deliver scalable analytics solutions. Mentor teammates and participate in agile delivery and production support.

Lead measurement strategy and operations for Pinterest27s tvScientific CTV campaigns. Build incrementality, attribution, MMM, and experimentation frameworks; create reporting templates and dashboards; partner with Sales, CS, Product, Engineering, and Analytics to ensure data quality and scalable pipelines; translate complex results into client-ready insights; drive measurement best practices and educate GTM teams.

Lead enterprise business strategy, portfolio analytics, operational reporting, and decision-support across Sales, Originations, Servicing, and Dealer Services. Drive analytics strategies to improve profitability and mitigate risk, oversee reporting and data architecture, partner with executives on business initiatives, and lead and mentor analytics teams while ensuring regulatory compliance and communicating insights to executive leadership and the Board.

Lead technical analytics for client and employer reporting: gather requirements, build/validate/automate reports and data files, perform UAT and dataset comparisons using SQL/Python/R, design monitoring and validation automations, and enable stakeholder self-service while applying healthcare claims and enrollment domain knowledge.

Build and operate ingestion and transformation pipelines, model and test core warehouse data, enable analytics and reporting, and maintain ML data infrastructure feeding matching and recommendation models. Partner with Engineering, Product, and Data Science to ensure reliable, documented, and trusted data at scale.

Own product analytics, financial tracking, and reporting for the Product & R&D organization. Build dashboards and financial models, define KPIs, monitor P&L and headcount, synthesize data from multiple systems, and coordinate cross-functional product operations and executive communications.