Top Data & Analytics Jobs

Analyze and improve manufacturing performance using metrics such as OEE, yields, cost, energy, quality, and waste. Develop dashboards, automated reporting, data pipelines, and performance visualizations. Support advanced process control, digital twins, machine learning, benchmarking, and digital transformation initiatives. Extract and preprocess data from SAP, SQL, and Oracle systems while collaborating with manufacturing leadership to identify efficiency, cost, and quality improvements.

Develops and supports applications, data structures, reporting, and production systems. Responsibilities include requirements analysis, data mapping, SQL development, testing, defect resolution, technical documentation, end-user support, data governance, project participation, and post-implementation reviews. The role also supports production monitoring, complex reporting, operational procedures, disaster recovery, and technical mentoring at higher levels. This is a hybrid position requiring residency and work within Arizona.

Analyze and report healthcare data while designing, maintaining, and optimizing ETL/ELT pipelines. The role requires SQL querying, data modeling and validation, dashboarding with Power BI and Excel, data governance, automation, and modernization of legacy systems. The analyst will collaborate with stakeholders to define data requirements and improve analytics and operational workflows in a regulated healthcare environment.

Own WireScreen’s robotics industry coverage as an internal and external subject-matter expert. Research and map global robotics subsectors, key players, technologies, supply chains, and industry developments. Monitor conferences and publications, engage with experts, collaborate with product and engineering teams to improve platform coverage, and write reports for customers and internal stakeholders.

Serve as a subject matter expert to analyze and improve enrollment processes, manage data integration and reporting, monitor enrollment and bad-debt trends, support fraud mitigation, and present actionable insights to stakeholders to optimize customer enrollment performance across the credit, fraud, and lifecycle journey.

Build and transform commercial data solutions using SQL and Databricks, create executive dashboards in Tableau and Power BI, and translate ambiguous business questions into actionable insights. Partner with commercial stakeholders on sales, retail-out, and distribution analytics; identify business trends, standardize reporting, and support enterprise self-service analytics and data maturity initiatives.

Leads Vitana’s data and technology strategy by building centralized data architecture, warehouses, pipelines, integrations, reporting, and governance. Serves as the technical leader across IT infrastructure, vendors, security, compliance, and technology implementations. Partners with executives and practice leaders to translate business needs into scalable solutions, improve data quality, support practice integrations, and connect technology investments to operational and financial outcomes.

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.

Own and evolve WorkOS’s internal data platform, including ingestion, orchestration, Snowflake, dbt models, data governance, reverse ETL, semantic views, and AI-enabled data workflows. Ensure pipeline reliability, freshness, security, and scalability while partnering with Product, Finance, RevOps, GTM, Engineering, and Security. Build monitoring, runbooks, CI/CD gates, access controls, masking policies, and infrastructure automation across AWS and Kubernetes.

Two-year early-career rotational program with three cross-functional assignments focused on data engineering and analytics. Participants create analytical reports, work with machine learning and artificial intelligence, lead intensive business projects, and develop technical, interpersonal, and leadership skills. The program provides exposure to the full data lifecycle, business strategy, and continuous improvement, with potential placement into a post-program role.