Top Data & Analytics Jobs

Lead complex data and financial analytics projects, applying advanced modeling techniques to improve business processes and influence executive decisions.

Independently manage complex data intake, validation, and quality for procedural analytics. Map, normalize, and validate EMR-sourced datasets; resolve escalated data issues; support implementations, tooling enhancements, and customized analyses. Lead projects, mentor junior staff, and translate findings into actionable recommendations for internal teams and members.

Administer and optimize enterprise Power BI and Microsoft Fabric platforms, handle capacity planning, telemetry monitoring, governance, migrations, access controls, and incident response. Collaborate with business and development teams, document best practices, and participate in on-call and after-hours deployment rotations.

Maintain and evolve the data ecosystem for fraud detection and analytics: build and operate ELT/ETL pipelines, integrate multiple data sources, implement monitoring/alerting, automate processes, collaborate with data scientists and commercial teams, mentor junior engineers, and communicate technical work to non-technical stakeholders.

Provide senior operational support for index, fund, product, and account reference data. Ensure data accuracy and timely delivery, lead data quality controls, resolve complex issues, drive process improvements and automation, support onboarding and business continuity, manage vendor and IT interactions, and lead data-related projects and documentation.

Design, build, and maintain large-scale data pipelines and APIs for Ventura OS. Optimize data processing workflows, integrate ML models into production, ensure data quality and observability, and collaborate across teams to drive architecture and data infrastructure decisions for streaming and content recommendation use cases.

Manage and optimize the Business Intelligence engineering team, develop BI strategy, oversee project management, and ensure data accuracy.

The Data Analyst will collect, clean, and analyze data to support business decisions. Responsibilities include creating reports and dashboards and presenting insights to stakeholders.

The Analytics Engineer will build and optimize data systems, analyze catalog performance, and collaborate across teams to enhance decision-making processes.

As an ETL Data Engineer, you'll design and maintain data integration processes using Python and Azure Synapse Analytics, ensuring data accuracy for insights. You'll collaborate with teams, implement data quality checks, and contribute to performance tuning and data modeling.

The Azure Data Engineer will design and develop ETL processes, utilizing Python and Azure Synapse Analytics, to manage data integration and ensure data accuracy. Responsibilities include performance tuning, data modeling, and collaboration across teams.

Lead design and delivery of enterprise-grade CRM and analytics data integration solutions. Build and operate batch and near-real-time ETL/ELT pipelines, Python automation, and SQL/NoSQL data models. Ensure data quality, security, observability, and operational ownership while partnering with architecture, application, and business teams.

Analyze transaction data to detect fraud, develop controls and rule-engine logic, automate data workflows, build dashboards and reports, partner with data science on fraud models, monitor model performance, and advise stakeholders on fraud strategy and risk.