Top Hybrid Data & Analytics Jobs

Leads the marketing analytics function and enterprise analytics strategy across client reporting, retailer insights, business intelligence, measurement, and operational analytics. Partners with executives to translate complex data into strategic recommendations, oversees advanced analytics and BI platforms, and manages reporting, governance, forecasting, attribution, and ROI analysis. The role also leads, coaches, and develops a high-performing analytics team while collaborating across sales, finance, operations, client services, and technology.

Leads the marketing analytics function and enterprise analytics strategy, covering client reporting, retailer insights, business intelligence, measurement, forecasting, attribution, ROI, and operational analytics. Partners with executives to translate complex data into strategic recommendations, oversees dashboards, BI platforms, data governance, and analytics solutions, and leads a high-performing analytics team. Collaborates across Sales, Finance, Operations, Client Services, and Technology to drive growth, retention, and performance.

Provides advanced analytics consulting and advisory support to healthcare clinical and business stakeholders. Queries internal and external data sources, develops insights and dynamic dashboards, and leads multiple analytics initiatives. Partners with senior leaders and cross-functional teams to translate business cases into execution, delivering high-quality analysis under tight deadlines. Requires strong SQL, Python or R, data visualization, communication, and healthcare or insurance industry expertise.

Leads people analytics initiatives by building scalable workforce datasets, data models, dashboards, and executive insights. Performs statistical analysis, forecasting, scenario modeling, and cross-system workforce analytics using Workday and enterprise data platforms. Partners with HR, HRIS, IT, Finance, and business stakeholders to improve data quality, governance, and decision-making. Guides project delivery, supports predictive and AI-enabled analytics, mentors analysts, and serves as a senior technical escalation point.

The Senior Data Analyst will source, validate, and reconcile data supporting forecasting, purchasing, inventory planning, and reporting. Responsibilities include auditing forecasts and operational outputs, identifying data quality issues, rating results, automating recurring checks and workflows with AI, documenting planning processes, and integrating tools with merchandising and operating systems. The role collaborates with planning, merchandising, sourcing, logistics, eCommerce, wholesale, and finance teams to deliver reliable, decision-ready data.

Leads governance, stewardship, quality control, and integrity for commercial data across customer, sales, pricing, and related domains. Establishes standards and controls, resolves complex data-quality issues, and drives sustainable process improvements. Partners with commercial, analytics, data science, engineering, and IT teams to deliver scalable data, analytics, and AI-enabled solutions. Oversees responsible AI application, automation, validation, enrichment, and anomaly detection while translating technical recommendations for business stakeholders.

Designs and scales Snowflake-based healthcare data and AI solutions, including Cortex AI agents, LLM functions, semantic search, RAG pipelines, Streamlit applications, and Snowpark data workflows. Builds ELT pipelines, optimizes Snowflake performance, implements Data Vault or Medallion architectures, and manages governance, security, HIPAA compliance, lineage, and access controls. Partners with technical and clinical stakeholders while serving as a Snowflake subject matter expert.

Lead analytics and reporting for Sales Enablement by analyzing campaign, product adoption, and customer data; creating dashboards, recurring reports, and executive-ready insights; establishing KPIs; improving workflows; and automating manual processes. The role partners with Data Science, Product, Sales Operations, Marketing, and Customer Success while translating business questions into data-driven recommendations.

Designs, builds, and optimizes enterprise Databricks Lakehouse pipelines and data products using Spark, Delta Lake, SQL, and Python. Leads complex data initiatives, production support, governance, CI/CD, workflow orchestration, monitoring, and modernization of legacy SQL Server solutions. Partners with stakeholders, optimizes performance and cost, mentors engineers, and drives engineering standards across Azure data platforms.

Reviews annotated sensor and map data for quality, identifies recurring issues, and recommends solutions. The role prepares reports, maintains annotation policies, develops training documentation, performs data annotation, tests internal tools, reports bugs, and creates visual assets. It also collaborates with stakeholders, partners, annotators, project managers, and engineers while supporting on-road operations and evolving program priorities.