Top Senior Data & Analytics Jobs

Leads Columbia’s North America Commercial Analytics function, unifying reporting, metrics, data sources, and decision-making across wholesale, DTC, marketing, merchandising, and consumer insights. Builds analytics capabilities, operating rhythms, and high-performing teams while translating commercial, consumer, market, and financial data into growth and profitability recommendations. Partners with technology teams on analytics platforms and champions AI-enabled decision support. Advises executive leadership through strategic analysis and fact-based insights.

Build and operate streaming and batch data pipelines for energy-storage telemetry. Design reliable, query-ready time-series and event datasets using open table formats, orchestration frameworks, AWS, and infrastructure-as-code. Lead technical designs, partner with field operations and engineering teams, support on-call operations, and mentor engineers while improving data reliability and engineering practices.

Own Serval’s complete data function as its first dedicated data hire. Build a unified warehouse, ETL/ELT pipelines, data models, quality and governance systems, documentation, and self-serve analytics. Partner with technical and business teams to define trusted metrics, consolidate product and SaaS data, and create AI-powered internal data tools. Select the data stack, establish engineering standards, and support scalable, cost-conscious infrastructure.

Serves as a senior analytical resource translating business needs into scalable data, reporting, and dashboard solutions. Designs reusable analytical datasets and data marts, applies advanced SQL, improves data quality and governance, and develops performance reporting. Partners with stakeholders and technology teams, provides technical leadership and coaching to analysts, supports code reviews, and strengthens analytics standards, usability, and scalability.

Leads College Board’s Operations analytics strategy and team, developing forecasting, predictive modeling, optimization, cost assessment, and decision-support capabilities. Partners with senior leaders across Operations, Product, Program, Technology, and Finance to improve execution, customer experience, efficiency, and cost savings. Responsibilities include setting technical direction, embedding analytics into operational decisions, presenting insights, hiring and coaching analytics staff, and building future AI and data-infrastructure capabilities.

Leads and develops data engineering teams while designing governed, scalable data solutions using Databricks, SQL, and cloud technologies. Translates consulting and business needs into reusable data assets, governed access patterns, documentation, dashboards, APIs, and analytics capabilities. Partners with governance, security, compliance, architecture, product, analytics, and managed services teams to improve data quality, lineage, usability, security, operational support, and delivery speed.

Lead design and delivery of Snowflake-based data solutions, data models, ETL pipelines and data warehouse applications. Provide architecture direction, drive technology transformation and POCs, evangelize modern data architecture, collaborate with global stakeholders and Agile teams, and apply advanced analytics (ML/AI/GenAI) while ensuring data security and PII management.

Design, build, and maintain Databricks-based data platform and ETL/ELT pipelines. Collaborate with stakeholders, implement data quality checks and testing, monitor pipeline performance, document architecture, and coordinate cross-functional teams.

Manage, clean, validate, and analyze quantitative and survey data using SAS, R, and SPSS. Generate reports, data retrievals, summary outputs, surveillance reports, and presentation graphics. Review programs, error logs, variable definitions, weights, and data quality; document corrections and ensure protocol compliance. Merge data from multiple sources, support stakeholder reporting, and assist with data management processes and protocols.

Leads cross-functional data management and analytics projects for pharmaceutical and life sciences clients. Responsibilities include data warehouse development, ETL and schema design, data analysis, process optimization, client communication, project management, business development, and mentoring junior staff. The role also provides strategic guidance, develops reporting solutions, manages timelines and resources, and contributes to internal data platform initiatives.