Top Hybrid Data & Analytics Jobs

Own and expand Ramp’s AI spending research, including the Ramp AI Index, new adoption and ROI metrics, international analysis, and customer-facing insights. Produce research reports, visualizations, presentations, dashboards, and interactive tools for finance leaders. Translate data into recommendations for budgeting and AI strategy, collaborate with growth teams on distribution, and communicate findings through writing, events, and executive engagement.

Lead enterprise data strategy and delivery across data platforms, master data management, semantic layers, governance, quality, modeling, and pipelines. The role requires hands-on architecture leadership, executive stakeholder engagement, and delivery of complex multi-region platforms using Snowflake, cloud infrastructure, MDM, Collibra, dbt, and batch and streaming architectures.

Conduct market and competitor research, monitor industry trends, compile biographical and strategic profiles, and produce partner-ready reports and briefings using legal research platforms to surface business opportunities and support pitches for attorneys and firm leadership.

Owns Care.com's Voice of the Customer program, analyzing large-scale survey, review, account-management, and contact-center feedback. Leads a VOC Insights Analyst and translates quantitative and qualitative findings into actionable recommendations for Product, Design, Operations, and other stakeholders. Oversees NPS, CSAT, and customer-effort measurement frameworks, survey methodology, taxonomy, reporting, and program expansion. Uses AI and text analytics to identify themes and trends, influence roadmaps, and improve member experiences.

Own the technical infrastructure supporting Spotify’s revenue growth programs. Build and maintain dbt models, BigQuery pipelines, dashboards, reports, and LLM-enabled data workflows. Monitor pipeline health, resolve data issues with engineering and Insights teams, and translate sales needs into reliable data products that improve prioritization, outreach, and advertiser growth.

Lead master and reference data strategy, governance, operating models, and platform modernization for Everest’s global insurance business. Define requirements, target architecture, ownership, stewardship, controls, workflows, data quality standards, lineage, reconciliation, and regulatory practices. Partner with business and technology stakeholders to implement trusted records, hierarchies, taxonomies, automation, and governed self-service. Oversee operations, issue management, reporting, adoption, and continuous improvement across enterprise data platforms and products.

Principal technical leader responsible for architecting and operating relational data marts, dbt data products, semantic layers, and shared data services. Builds scalable solutions in Databricks, Delta Lake, and Spark; owns data products through testing, deployment, documentation, monitoring, and support. Establishes governed metrics, data quality, lineage, observability, and access controls while partnering cross-functionally to resolve ambiguity. Mentors engineers, improves reusable frameworks, and supports BI, data science, and AI use cases.

Produces scheduled reports, data refreshes, business review materials, incentive reconciliations, and health-score updates. Maintains data hygiene, version control, and reporting accuracy while identifying anomalies and supporting root-cause analysis. Develops analytical expertise and performs initial analyses under manager guidance. The role requires strong Excel skills, attention to detail, reliable deadline management, and exposure to SQL or BI tools.

Manage and develop a team of 4–6 analysts delivering customer reporting and analytics. Lead complex analyses, establish standards for rigor and reproducibility, oversee project delivery, present findings to stakeholders, and partner with Product and Engineering on measurement products and AI-enabled analytics tools. The role requires deep advertising measurement expertise, client-facing communication, dashboard development, and hands-on proficiency in SQL, Python, Excel, statistical methods, and analytics platforms.

Designs and implements scalable physical data models in Snowflake, translating conceptual and logical models into schemas, tables, and views. Collaborates with data engineering, architecture, governance, business, and technical teams on ETL/ELT, data integration, metadata, documentation, compliance, and pipeline optimization. Requires Data Vault 2.0, SQL, Snowflake, governance, and stakeholder management expertise, with pharmaceutical experience preferred.