Top Hybrid Data & Analytics Jobs

Partner with commercial and delivery teams to build scalable reporting, KPIs, dashboards and forecasts. Analyse sales, pre-sales and delivery performance to reduce time-to-revenue, improve deal velocity, and provide data-driven recommendations to drive commercial growth.

Analyze and engineer complex data to create metrics, dashboards, visualizations, integrations, and actionable recommendations. The role defines business requirements, develops ETL processes, integrates internal and external data sources, and communicates insights to cross-functional and customer-facing teams using Tableau, Power BI, Excel, SQL, Python, and .NET.

Coordinates day-to-day data enablement activities, including data entry, maintenance, cleansing, standardization, quality audits, issue resolution, user support, process documentation, and reporting on data quality metrics. Works with data managers and department partners to keep organizational data accurate, accessible, and usable while supporting data tools and workflows.

Conduct quantitative equity research using financial statements, holdings, company filings, and varied datasets. Develop valuation, business analysis, classification, narrative, and portfolio analytics; validate models before launch and investigate production issues. Document code and methodologies, review peer work, identify data-quality issues and edge cases, and communicate analytical findings to senior colleagues. The role requires strong equity fundamentals, Python and SQL expertise, rigorous research practices, and familiarity with AI-assisted research and validation.

Own data pipelines into and out of the warehouse, dbt models, data integrity, governance, identity resolution, reverse ETL, and quality monitoring across growth, lifecycle, and brokerage data. Partner with product, marketing, and operations teams to establish data contracts, ensure accurate and timely business metrics, and support regulated financial data requirements.

Leads Expedia Group’s data engineering, software engineering, AI, and innovation capabilities for Marketing Automation and MarTech. Sets enterprise technology strategy, oversees scalable data platforms, pipelines, APIs, integrations, governance, security, observability, and responsible AI foundations. Builds high-performing engineering teams, manages modernization and platform investments, enables analytics and experimentation, and partners with senior stakeholders to improve customer engagement, operational efficiency, and technology delivery.

Lead the strategy and governance for GTM analytics across pre-sales, post-sales, solutions engineering, forward-deployed engineering, and professional services. Establish trusted source-of-truth metrics, data models, semantic layers, self-service analytics, and AI-assisted querying. Partner with Data, Finance, Sales, and Services leaders to resolve metric definitions, improve data access, consolidate reporting, and guide cross-functional programs without direct authority.

Design, build, and operate batch, streaming, and hybrid data pipelines in a regulated healthcare environment. Develop dbt models in BigQuery, ingest structured and unstructured clinical data, and implement data quality, lineage, governance, and compliance controls. Support ML workflows, CI/CD, monitoring, incident response, and platform architecture. Collaborate with data scientists, clinical, quality, security, and product teams while mentoring engineers and establishing standards.

Build and own end-to-end data products, including pipelines, transformations, semantic models, dashboards, metrics, and AI-enabled workflows. Partner with business and technical stakeholders to turn ambiguous questions into trusted, maintainable solutions. Establish data quality testing, documentation, monitoring, and governance while improving architecture and automation. Use Snowflake, dbt, Power BI, and related technologies to support analytics across Marketing, Product, Finance, and Engineering.

Own Hometap’s product and marketing event-data ecosystem, including taxonomy, tracking plans, governance, Segment Protocols, schema validation, and source management. Partner with marketing, product, and engineering to define instrumentation and event specifications. Build monitoring for schema conformance, event volume, and property completeness, while documenting standards and managing event review and deprecation processes.