Top Senior Data & Analytics Jobs

Lead the architecture, design, implementation, and maintenance of data warehouse operations. Build scalable data storage, processing, integration, replication, transformation, and analytics solutions using Snowflake, AWS, Qlik tools, dbtLabs, and Astronomer. Apply data modeling, ETL, governance, quality, lifecycle management, SQL, and scripting expertise while troubleshooting engineering issues and collaborating with cross-functional stakeholders.

Leads an analytics team and uses advanced Tableau expertise to create impactful reports, dashboards, and data visualizations. Translates business questions into analytical approaches, works with complex datasets, and delivers data-driven insights to support business decisions. Responsibilities also include statistical analysis, data extraction, cleaning, transformation, stakeholder communication, people management, and prioritizing multiple projects.

Leads and coaches a data engineering team while contributing hands-on to platform architecture, data modeling, ETL pipelines, data quality, and analytics solutions. Designs trusted facts, dimensions, snapshots, and slowly changing dimensions using Snowflake, Databricks, dbt, and Airflow. Partners with stakeholders, security teams, vendors, and cross-functional groups on data strategy and controls, resolves production issues, supports incident response, and develops engineering talent.

Deliver advanced analytics across the remarketing lifecycle to optimize proceeds, cycle time, and channel performance. Build scalable analytics solutions, dashboards, and scorecards; monitor performance and run strategic tests; translate data into insights for stakeholders; mentor junior analysts; ensure data governance and quality; partner cross-functionally to align metrics and drive decision-making.

Lead enterprise analytics and data governance initiatives, build Power BI dashboards and Databricks/SQL pipelines, leverage Epic Clarity for healthcare insights, develop automated monitoring and surveillance analytics, and partner with business leaders to drive data-informed decisions.

Build and maintain automated data pipelines, deploy AI agents for operational analysis, create Tableau and Power BI dashboards, generate LLM-based metric summaries, improve data quality, automate reporting workflows, and provide predictive insights for diagnostics operations supply chain leaders. The role also gathers business requirements, performs ad hoc analysis, and manages multiple evolving technical requests.

Analyze and optimize e-commerce pricing strategies using sales, demand, customer behavior, competitive pricing, AI, and experimentation. Develop pricing models, measure elasticity, evaluate revenue and margin impacts, monitor competitor prices, and build dashboards, alerts, and scenario analyses. Translate analytical findings into recommendations and partner with Ecommerce, Marketing, Product, and Finance teams to improve profitable growth.

Lead the design, build, and maintenance of scalable data pipelines, architectures, and data products on Databricks and AWS. Partner with cross-functional teams, mentor engineers, implement CI/CD, optimize performance, and enforce data governance to support analytics and AI initiatives.

The Senior GC-MS GC-TQ Analyst operates and maintains GC-MS systems, performs complex analyses per EPA methods, ensures compliance, and aids method development.

Leads data analytics and operational improvement across a college’s administrative functions. Develops dashboards and executive reporting, standardizes workflows, evaluates process inefficiencies, translates business requirements into technical specifications, and partners with development teams on workflow systems. Manages improvement projects, change management, training, documentation, stakeholder reporting, and continuous system refinement across areas including procurement, inventory, HR, budgeting, and facilities.

Leads enterprise analytics engineering by designing semantic models, governing KPIs and metric definitions, and enabling trusted self-service reporting. Partners with business stakeholders, Data Engineering, and IT to translate business needs into scalable analytical frameworks and reliable data assets. Establishes governance, documentation, validation, and change-management practices while supporting advanced analytics and AI/ML readiness. Supervises analytics personnel through coaching, performance management, and professional development.