Top Hybrid Data & Analytics Jobs

Analyze card performance and customer behavior, design and evaluate A/B tests, build dashboards and KPIs, create financial models and business cases, partner with cross-functional teams, improve data infrastructure and reporting, and deliver executive-ready insights to optimize card growth, engagement, and profitability.

Lead development and delivery of analytical datasets and AI-enabled analytics for global real estate. Partner with stakeholders to translate business needs, design data solutions, enforce governance and quality, scale AI use cases, and deliver executive-level reporting and project management.

Analyzes customer, marketplace, product, financial, merchant, and transaction data to identify trends, risks, and growth opportunities. Builds analytical frameworks for new products, markets, and strategic initiatives; validates data sources and metrics; investigates anomalies; and develops actionable recommendations. Communicates insights through dashboards, presentations, and concise storytelling to senior executives, cross-functional leaders, and the Board. Partners with Product, Engineering, and Data teams to improve decision-making and uses emerging AI tools to accelerate analysis.

Gather, clean, and transform data; build dashboards, reports, and visualizations; perform statistical analysis; develop enterprise data models; ensure data quality; support business users with self-service analytics; maintain data education resources; and translate findings into actionable recommendations.

Owns the enterprise Power BI ecosystem, including data modeling, ETL/ELT pipelines, dashboards, reporting, administration, governance, security, and support. Leads BI implementations, platform maintenance, testing, documentation, process improvements, stakeholder training, and adoption of Microsoft Fabric, Databricks, and AI-enabled analytics. Requires strong Power BI and Azure Data Factory expertise, business requirements translation, analytical problem-solving, communication, and potential people leadership. Travel up to 20% domestically and internationally is required.

Design, build, and maintain end-to-end data pipelines and analytics models using DBT, SQL, and Python. Create dashboards, prototype data products, manage GitHub-based analytics workflows, and partner with engineering, product, and clients to deliver actionable insights for external customers.

Design, build, optimize, and maintain scalable batch and near-real-time data pipelines across on-premises and cloud platforms. Develop Snowflake data models, manage enterprise data integration and governance, implement data quality controls, and support reporting and analytics. Collaborate with data scientists, analysts, infrastructure, DevOps, privacy, and compliance teams. Troubleshoot pipeline issues, monitor performance, participate in architecture and Agile development activities, and mentor associate data engineers.

Design, maintain, and upgrade Power BI content; partner with stakeholders to define metrics; build underwriting and profitability alerts; automate finance analyses; troubleshoot data warehouse issues and coordinate IT solutions.

Designs, builds, and maintains scalable data pipelines, data marts, enterprise data platforms, and ETL processes. Integrates diverse data sources, improves data quality and performance, and supports secure analytics infrastructure using Microsoft Fabric and Azure. Develops Tableau and Power BI dashboards, collaborates with cybersecurity and cross-functional teams, manages project deliverables, documents processes, and trains team members on data organization and interpretation.

Lead Product Data & Analytics, building and scaling a team of data scientists, analytics engineers, and analysts. Own roadmap, standards, experimentation, metrics, and data products; embed analytics into product development; partner with cross-functional leaders; hire and mentor senior staff and report impact to execs.