Top Hybrid Senior Level Data & Analytics Jobs

This role involves enhancing data quality through analysis and reporting, collaborating with teams to modernize data infrastructure and drive business insights.

Lead analytical method validation and drive process excellence initiatives. Collaborate with CDMOs, support quality systems, and manage documentation for regulatory compliance.

As a Senior Data & Integrations Engineer, you will design and govern data architecture, manage integrations, and ensure data reliability and scalability while collaborating with various teams.

As a Senior Data Engineer, you will design ETLs for large customer datasets, improve integration tools, and mentor other engineers, impacting customer onboarding and data accuracy.

The VP, Analytics leads the analytic strategy and delivery across client engagements, focusing on data management, performance optimization, and hands-on contribution to advanced measurement. This role influences decision-making and ensures analytics ties to meaningful business outcomes, while mentoring a high-performing analytics team and collaborating cross-functionally.

As a Senior Product Analyst at Persona, you'll lead fraud analytics investigations, manage a team of fraud analysts, and provide actionable recommendations to enhance fraud detection and prevention capabilities.

Responsible for establishing a Data Architecture practice, adopting methodologies, designing solutions, and collaborating with stakeholders. Coaches lower-level professionals and manages ideation, design, implementation, and compliance with IT standards.

This role involves leading the Data & AI team, building modern data platforms using Microsoft technologies, overseeing project delivery, and mentoring team members while engaging with clients.

Lead product analytics, metric governance, and the semantic layer. Build recurring reporting and dashboards, ensure data quality and instrumentation, diagnose performance shifts, support experimentation and segmentation, and translate insights into product and business decisions while scaling an analytics function.

Design and build scalable platforms for data ingestion and storage, collaborate with hardware engineers, and define engineering processes at Sift.