Top Data & Analytics Jobs

Lead analytics engineering by developing scalable data models, defining analytics requirements, establishing company-wide data quality standards, and delivering reliable data products. Partner with analysts, engineers, product managers, and other stakeholders to improve data accessibility and decision-making. The role requires advanced SQL, Snowflake, dbt, BI tools, data modeling, testing, documentation, version control, and CI/CD experience, along with fintech industry knowledge.

Build and maintain ETL/ELT pipelines to move product data into analytics-ready stores (Postgres, data lake, warehouse). Design and optimize data models, ensure data quality and documentation, support ad-hoc research requests, and collaborate with research and engineering teams to enable reproducible analytics.

As a Quantitative Developer, you'll innovate and enhance quantitative methods, develop custom tools, maintain data pipelines, and collaborate with researchers for advancing investment strategies.

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.

Build and operate governed Finance data infrastructure on Databricks, including scalable pipelines, integrations, semantic layers, data-quality controls, observability, and AI-enabled services. Partner with analytics and enterprise teams on architecture, data contracts, security, recoverability, and production ownership. Optimize platform costs through FinOps practices and use AI coding assistants while validating performance, correctness, and security.

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.

Build and optimize enterprise data warehouses, data lakes, and scalable batch and streaming pipelines. Support Snowflake and Databricks ecosystems, resolve ETL/ELT bottlenecks, automate workflows with Airflow and Control-M, and manage AWS-based infrastructure. Develop production-grade Python, SQL, and shell solutions while applying DevOps, CI/CD, IaC, and data modeling practices. Lead incident management, root cause analysis, operational metrics, and Agile collaboration with data and platform teams.

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.