Top Data & Analytics Jobs

Design, build, and maintain scalable batch and real-time data pipelines and platform components. Produce curated datasets, ensure data quality, observability, and lineage, and collaborate cross-functionally to deliver data products that support analytics, experimentation, and ML.

Technical lead on the Distribution Center data team building and scaling ETLs and data integrations using PySpark and DBT. Design robust pipelines to process large customer datasets, improve onboarding tooling, mentor engineers, manage contractors, and collaborate cross-functionally to support ML-driven grocery solutions.

Lead GTM causal measurement strategy to quantify sales headcount and incentive incrementality. Design, validate, and scale advanced causal models in R/Python, operationalize production-grade data pipelines with engineering teams, and translate results into executive decision-making to optimize global revenue and ROI.

Support analytics for a large multi-product client: implement measurement frameworks, run test-and-learn programs, validate data, analyze attribution/brand lift/MMM outputs, produce dashboards and actionable insights, and mentor analysts while coordinating with cross-functional and data partners.

As a Market Data Operations Analyst, you'll manage market data vendors, support procurement processes, and ensure compliance with data governance.

The Data Integration Lead designs and manages data ingestion pipelines, ensuring data integrity and security while supporting ETL processes in classified environments.

Manage and govern global product data across PIM and ERP systems: improve data architecture, enforce governance, ensure data quality and enrichment, enable omnichannel and eCommerce use cases, coordinate global teams, identify automation opportunities, and support data quality investigations and roadmap planning.

Manage day-to-day data operations including issue triage, vendor coordination, root-cause analysis across CRM, data warehouse, and vendor feeds. Create and track tickets, validate fixes, produce ad-hoc reports, support Tableau/Power BI, and drive data quality and governance improvements while liaising between business stakeholders, IT, and external vendors.

Design, build, and maintain scalable data pipelines and platform tools; define canonical data models; deploy and operate workflow managers (Airflow/Jenkins); work with cloud data tools (Redshift, EMR) and infra (Kubernetes, Terraform); implement data security controls; mentor junior engineers and collaborate with data scientists, analysts, and product teams.

Design, build, and maintain reliable data pipelines and data warehouse artifacts. Collaborate with engineering, product, and research teams to prototype solutions, document data products, and ensure quality and scalability.