Top Data & Analytics Jobs

Supervises Data Services team focusing on data engineering and operations, ensuring alignment with IT policies, data governance, and operational reliability of data products.

Lead and mentor data engineering teams to design, build, and govern enterprise data warehouses, lakes, and lakehouses. Architect scalable ETL/ELT and streaming pipelines, drive cloud migrations, enable BI/AI initiatives, and partner with Finance, Operations, and Supply Chain to deliver analytics and operational reporting.

Build governed gold-layer data models and a single-source metrics layer in Snowflake (dbt); create and optimize dashboards in enterprise BI tools; use AI coding agents and AI-assisted tooling to accelerate development; ensure data quality, governance, and consistency; collaborate with data engineering and stakeholders to deliver trusted analytics for internal and client-facing use.

Design and implement scalable Azure-based data architectures and analytics solutions, lead delivery teams, support pre-sales, drive DevOps/CI-CD, mentor junior staff, define data strategy, governance, migrations, and oversee project delivery and backlog management.

Join SignalFire's talent network to be considered for data engineering roles at VC-backed startups. Responsibilities include designing and maintaining batch and real-time pipelines, building data models and cloud data platforms, enabling analytics and ML pipelines, ensuring data quality/observability and governance, integrating varied data sources, improving performance and cost efficiency, and partnering cross-functionally to define data architecture and tooling.

The AI Patterns Business Analyst will analyze customer engagement data, categorize documentation, and provide weekly updates on customer signals to aid sellers.

Lead North America marketing analytics product portfolio, evolve MMM to causal and AI-native methods, prioritize roadmap and epics, oversee data engineers and scientists, drive adoption and value measurement for marketing effectiveness.

Undergraduate quant research intern to analyze financial datasets, clean and validate data, build simple models and backtests, write Python analysis and visualizations, and summarize results. Work collaboratively with researchers, traders, and engineers to develop and test systematic trading ideas.

Support and maintain BI applications, troubleshoot issues, analyze user requirements to recommend reporting or application solutions, and design, build, test, and maintain reporting and data solutions.

Design, build, and own the analytics data layer: curated models, marts, and semantic metrics. Migrate SQL Server models to Snowflake, produce well-tested SQL, implement monitoring/validation, ensure data accuracy, document lineage, and partner with Data Engineering and business stakeholders to enable reliable, self-serve analytics.