Top Data & Analytics Jobs

Lead and build a marketing analytics function to connect marketing activity to revenue. Design attribution and unified measurement frameworks, quantify pipeline contribution, optimize channel mix and ABM, build forecasting and predictive models, ensure clean data infrastructure, and hire/manage a small analytics team. Partner with RevOps, Sales, and marketing teams to drive data-driven budget and planning decisions.

As an Analyst in GTM Incentive Management, you will support sales incentive programs, analyze performance data, and enhance operational systems.

As a Messaging Pricing Lead at Braze, you'll manage vendor contracts and pricing for messaging solutions, analyze data, optimize pricing strategies, and collaborate with various stakeholders to drive growth and profitability.

The Senior Data Analyst will perform hands-on analytical work using SQL, design A/B tests, develop dashboards, and partner cross-functionally to drive data-informed decision-making across various teams.

The Senior Director will design and govern the enterprise-wide data architecture, lead the analytics team, and ensure data reliability for scalable decision-making across various functions.

Partner with Customer Success and CS Ops to build post-sales analytics: customer health scoring, renewal and renewal pipeline reporting, billing and support signal analysis, and expansion/upsell dashboards. Own dashboard ecosystem, translate stakeholder requests into scalable reporting, collaborate with Finance and Data Engineering, and leverage AI tools to accelerate analytic workflows and maintain data quality for retention and expansion decision-making.

The eCommerce Web Analyst supports teams by analyzing eCommerce data, creating dashboards, conducting A/B tests, and ensuring data accuracy to inform business strategies.

Lead data and software QA for enterprise data platforms: define testing strategy, build automated test frameworks, validate ETL/ELT and data transformations, run data quality checks and reconciliations, test APIs and data products, analyze datasets with SQL to find defects, drive root-cause resolution, participate in Agile ceremonies, and mentor team members to improve quality practices.

Lead and grow a data engineering team that designs, builds, tests, and operates large-scale data pipelines and warehouses. Partner cross-functionally to translate requirements, ensure data quality, observability, SLAs, security, and governance, and drive automation and performance for analytics, ML, and product use cases.

Own and operate the iMData platform: design and build Databricks-based ETL pipelines using PySpark and medallion architecture, create gold-layer star schemas, migrate assets from Synapse to Databricks, implement CI/CD and Terraform IaC, ensure data security and observability, mentor junior engineers, and collaborate with stakeholders and ML engineers to deliver production-grade analytics and AI-ready data.