Top Data & Analytics Jobs

As an ERP Analyst I, you will assist in configuring ERP systems, support data migration and testing, document requirements, optimize workflows, and participate in training sessions, while gaining hands-on experience with ERP systems.

Lead cross-functional analytics to inform clinical and operational decisions: build Tableau dashboards, create dbt analytical models, analyze large healthcare datasets (claims, EHR, HIE) with SQL, respond to ad-hoc requests via JIRA, and collaborate with product and engineering to improve data capabilities.

Lead commercial analytics and reporting for merchant programs: build KPIs and dashboards, automate reports, monitor performance and forecasts, translate data into actionable insights for clients and senior stakeholders, support optimization and collaborate with corporate data teams.

Founding data engineer to design and build Payabli's data platform: architect lakehouse/warehouse, build batch and streaming pipelines, model canonical datasets, ensure data quality/observability, enforce access/masking/lineage for regulated financial data, and enable analytics/ML feature pipelines while establishing team standards and CI/CD.

The Lead Data Engineer will design, implement, and maintain data pipelines for mission-relevant data, ensuring compliance with security frameworks and optimizing data accessibility and interoperability across mission systems.

The Quantitative Researcher will manage yield opportunities, design algorithms, perform risk analysis, and collaborate with engineers on DeFi strategies.

Lead and grow SQUIRE's Data organization as a player-coach, owning long-term data architecture, building reliable Snowflake pipelines, setting standards for modeling and data quality, hiring and budgeting for a 5+ person team, partnering cross-functionally, auditing integrations, and enabling AI/LLM use cases while remaining hands-on for high-risk technical work.

Build and maintain API-based data pipelines, analyze supply chain metrics, create dashboards and alerts, perform root-cause analysis, define KPIs with stakeholders, and document data models and integrations to improve logistics performance.

Design, build, and deploy data pipelines, databases, and AI-enabled automation to improve manufacturing test throughput, yield, and reliability. Integrate test systems and IoT sensors, support root-cause analysis, develop dashboards and alerts, and work hands-on with production teams for on-floor troubleshooting and sensor/validation tasks.

Design and maintain production data pipelines and architecture across Snowflake and Databricks, scale Terraform deployments, implement data governance, build demo data processes, and collaborate cross-functionally to support analytics and product use cases.