Client is focused on delivering therapeutic and scientific breakthroughs in areas of critical patient need spanning psychiatry & neurology, oncology, urology, women's health, rare disease, and cell & gene therapies.
The company's diverse portfolio includes several marketed products and a robust pipeline of early- to late-stage assets. Building on Client's 125-year legacy of innovation, CLIENT leverages proprietary in-house technology platforms and advanced analytics capabilities to accelerate discovery, development, and help bring novel therapies to patients sooner. CLIENT is a Client company.
Job Overview:
We are currently seeking a dynamic, motivated, and highly experienced individual for the position of Contractor, Senior Data Engineer that is responsible for the design, development, and optimization of enterprise-scale data infrastructure and pipelines.
With deep technical expertise and over a decade of experience, this individual supports the engineering strategy, ensures data platform scalability, and delivers high-quality data solutions.
This individual excels in technical execution, ensuring data is accessible, reliable, and secure across the organization.
This is a Contract role and not a direct hire with CLIENT.
Job Duties and Responsibilities:
Data Pipeline Development
Design scalable systems and build complex, end-to-end ETL (Extract, Transform, Load) pipelines to move data from various sources to data warehouses.
Data Governance & Security
Enforce strict data quality standards and ensure all system designs meet security compliance requirements.
Leadership & Strategy
Mentor junior engineers, translate complex business requirements into technical solutions.
Performance Optimization
Continuously monitor and troubleshoot data pipelines and databases to improve processing speed, scalability, and cost-efficiency.
Collaboration & Stakeholder Support
Ensure implemented Data Products meet the vision and goals of Data Consumers.
Documentation & Best Practices
Enforce and adhere to best practices for technical documentation related to architecture, transformation logic and coding standards.
Experience and Education: Must have:
10+ years of prior experience as a Data Engineer working directly with Data Warehouses, Data Lakes, ELT/ETL, Data Pipelines
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field
Languages: Advanced proficiency in SQL and Python
Cloud Platforms: Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.
Data Warehouses & Frameworks: BigQuery or Redshift.