Top Data & Analytics Jobs

Design, build, and maintain scalable data pipelines, data models, ETL/ELT, and BI solutions. Collaborate with data scientists and stakeholders to improve data quality, accessibility, and PHI security. Develop and document workflows, optimize processing/storage, support data warehouse and visualization, and adopt AI tools to drive data-informed outcomes.

Build and maintain scalable monitoring solutions and dashboards to track production, campaign, and operational data. Analyze large-scale datasets to detect anomalies, perform root-cause investigations with Engineering and Production Operations, and deliver actionable insights to improve platform reliability and operational efficiency.

Lead end-to-end data migration strategy and execution for complex franchise partners—perform discovery, map legacy data, troubleshoot imports, align stakeholders, and build scalable playbooks to standardize data delivery and ensure seamless platform transitions.

Design, develop, and maintain scalable data pipelines and ETL in Azure; ensure data quality, governance, and compliance; support Power BI analytics; troubleshoot pipeline performance; document architectures; and collaborate with BI and business stakeholders to translate requirements into technical solutions.

As a Data Engineer, you will leverage AI tools, develop data models, and build scalable data pipelines while partnering with cross-functional teams to enhance user experiences and automate workflows.

Design, develop, and maintain dimensional data models, data warehouses, and data marts. Translate business requirements into scalable data structures, build fact and dimension tables, perform SQL development, ETL/source-to-target mapping, data profiling, testing, and validation. Collaborate with stakeholders, mentor peers, and ensure data quality and alignment with enterprise architecture.

Lead enterprise BI across multiple brands: develop dashboards and executive scorecards (preferably QuickSight), define and govern KPIs/OKRs, ensure a single source of truth, partner with business and tech teams, drive data governance and quality, and collaborate with analytics engineering on scalable data pipelines.

Own analytics for consumer subscriptions (acquisition, conversion, retention, churn, revenue, pricing). Build dashboards, run statistical analyses and experiments, identify growth opportunities, ensure data integrity with monitoring and audits, write ETL/analysis code, and translate findings into strategic recommendations.

Build and operate GCP-native data pipelines and lakehouse infrastructure using Airflow, dbt, and BigQuery. Design layered data models, manage ingestion (batch and streaming), implement observability and governance, and maintain CI/CD workflows to deliver reliable analytics for MLB stakeholders.

Lead CT's BI function by maintaining KPI dashboards and data infrastructure, delivering MBR/QBR metrics and financial analysis, building cost and demand forecasting models, partnering across data, engineering, and operations, and tracking AI automation impact to inform leadership decisions and vendor staffing.