Top Hybrid Data & Analytics Jobs

Data Engineer Interns will support analytics platform enhancements, data modeling, data exploration, pipeline maintenance, troubleshooting, optimization, documentation, and stakeholder collaboration. The role focuses on building data products, supporting AI-enabled analytics, and translating business needs into data requirements. Candidates should be enrolled in a quantitative degree program and have foundational knowledge of business intelligence, databases, data modeling, SQL, and data visualization.

Leads enterprise data integration and engineering capabilities, including APIs, middleware, ELT pipelines, data governance, master data management, and cloud analytics platforms. Designs secure, compliant integrations across ERP, CRM, clinical, research, quality, finance, and commercial systems. Establishes architecture standards, data quality controls, monitoring, validation, and support processes while coordinating internal engineers, vendors, and business stakeholders. The role also provides technical leadership for trusted datasets, regulatory compliance, operational reliability, and commercialization readiness.

Develop and maintain scalable data pipelines and infrastructure using GCP services including BigQuery, Dataform, and Airflow. Optimize data processing for performance and cost, implement data quality testing, build data models and reusable components, and establish CI/CD practices. Collaborate across teams, contribute to architecture and documentation, mentor junior engineers, and apply AI tools to improve engineering workflows.

Own and improve ETL pipelines, investigate and validate analytics systems, optimize performance, cost, and availability, and design scalable data platforms. Collaborate with data scientists to deliver dashboards, insights, and client-facing data pipelines using strong software engineering practices.

As a Data Engineer, you will design, build, and manage data pipelines, improve data architecture, ensure accuracy, and collaborate with various teams.

The Associate Director develops and executes pricing strategies, analyzing market dynamics, leading pricing initiatives, and ensuring compliance in the pharmaceutical industry.

Partner with product teams to build data products, dashboards, and self-service AI/agent tooling. Own product metrics, run exploratory and ad-hoc analyses, improve data quality and governance, and translate analysis into clear recommendations to drive product OKRs.

Collect, analyze, and interpret complex datasets to create and maintain customer-facing Tableau reports; collaborate with customer services and development teams to scope reports and data models; investigate data accuracy issues and communicate insights to stakeholders.

Build, own, and monitor end-to-end data pipelines using Snowflake, Airflow, Fivetran, and DBT. Write advanced SQL and Python for ETL, model raw data into marts, enforce data quality checks, diagnose and fix deep data issues, and optimize database performance.

Apply mathematical modeling, statistical analysis, and systems optimization to evaluate and improve NexusOne platform performance. Define and validate data requirements, analyze pipeline throughput and governance compliance, and present findings to stakeholders. Collaborate with engineering and delivery teams to modernize legacy systems (Spark/Airflow), enable AI pipelines, and recommend NexusOne configurations to meet performance, compliance, and AI readiness goals.