Top Data & Analytics Jobs

Build and maintain data pipelines, integrations, models, warehouses, and cloud data infrastructure. Support data quality, governance, security, monitoring, incident response, documentation, and downstream analytics. Use Python, SQL, Databricks, Azure, dbt, and related tooling in a code-first, agile environment. Collaborate with analytics engineers and stakeholders while developing data engineering skills under mentorship. Participate in planned maintenance and occasional after-hours support for critical data operations.

Build and maintain scalable data infrastructure, pipelines, workflows, and large-scale data processing systems. Develop Python- and SQL-based solutions, integrate data from multiple sources, support machine learning model deployment and MLOps, monitor pipeline health, troubleshoot issues, and ensure data quality. Collaborate with data scientists, analysts, and stakeholders while documenting processes and applying data governance and security best practices.

Lead research on the macroeconomics of AI by authoring flagship reports, building quantitative forecasting models, integrating bottom-up semiconductor and datacenter data into macro estimates, developing LLM-driven research pipelines, performing econometric analysis, and communicating findings to investors, policymakers, and the public.

Owns the program reporting and analytics function, including dashboard architecture, reporting migration, data governance, data integrity, trend analysis, forecasting, and executive decision support. Leads reporting analysts and document control staff, maintains deliverable reporting accuracy, establishes metrics and quality standards, and ensures audit-ready traceability. Requires advanced Power BI, Excel, and reporting leadership experience in a program environment.

Supports end-to-end market research projects, including questionnaire and discussion guide development, data collection, quality control, analysis, visualization, reporting, and client-ready deliverables. Collaborates with internal teams and subcontractors while developing expertise in quantitative and qualitative research methodologies, software, and technology platforms. The role requires strong communication, analytical thinking, organization, attention to detail, and eagerness to learn.

Designs and maintains scalable enterprise data architectures and ETL/ELT pipelines on Microsoft Fabric and Azure. Responsibilities include developing Python-based data solutions, optimizing Fabric warehouses and lakehouses, implementing governance, security, lineage, monitoring, and CI/CD, and integrating diverse data sources. The role partners with data science, machine learning, business intelligence, engineering, and business teams to support analytics and model training while improving platform reliability, scalability, and cost efficiency.

Provides business intelligence supporting supply chain and materials management decisions. Develops reports, analytical tools, forecasts, and presentations using internal and external data. Researches industry trends, competitive positioning, financial performance, customer insights, and market risks. Documents business processes, promotes analytical methods, and creates training materials for business users and executives.

Leads data engineering teams responsible for designing, developing, and maintaining scalable data systems, integrations, pipelines, warehouses, and governance solutions. Provides technical leadership, mentorship, architecture guidance, and cross-functional coordination to meet business requirements, service-level agreements, compliance standards, and operational goals. Evaluates emerging technologies and oversees internal and outsourced resources supporting master data management, analytics, data warehousing, and enterprise information systems.

Actuarial Summer Interns will develop insurance industry expertise, perform actuarial analysis, and lead independent analytical projects under the supervision of experienced actuaries. The role is fully in-office in Reno, Nevada, and focuses on building technical problem-solving skills within the Actuarial and Analytics team.

Analyze large datasets to identify opportunities that improve customer experience and profitability. Build and automate reporting, develop quantitative analyses and visualizations, and provide strategic recommendations to senior leaders. The role uses Excel, SQL, Snowflake, R, and Tableau while collaborating across teams, managing multiple project streams, and designing and implementing new products and solutions.