Job title: Senior Data Engineer
Job type: Contract
Contract Length:12 months
Rate: $90 per hour
Role Location: United States
The Company:
This organization is a global leader in life sciences and clinical diagnostics, developing innovative tools and technologies that support research, discovery, and improved human health. Its products and platforms are used by scientists and healthcare professionals worldwide to drive meaningful advances in medicine.
The company is known for its high standards of quality, innovation, and scientific rigor, as well as a collaborative, purpose-driven culture. Employees work on mission-critical technology and data platforms that directly contribute to breakthroughs with real-world impact.
This is an opportunity to join a science-led, globally respected organization where technology and data play a key role in improving lives.
Role and Responsibilities:
We are seeking a Senior Data Engineer to join a growing data team supporting enterprise-wide data initiatives. This role is responsible for designing, building, and optimizing scalable data pipelines and architectures, with a strong focus on creating master data repositories for critical business data.
You will work closely with cross-functional stakeholders to enable reliable, high-quality data delivery across multiple systems and products. The ideal candidate is an experienced data engineer who enjoys building data platforms from the ground up, improving data flow, and supporting diverse analytical and operational use cases.
- Design, build, and maintain scalable, reliable data pipeline architectures that support enterprise analytics and operational needs
- Develop and manage master data repositories for critical business domains, ensuring consistency, accuracy, and accessibility
- Assemble and optimize large, complex datasets that meet both functional and non-functional business requirements
- Build and enhance ETL/ELT pipelines for extracting, transforming, and loading data from diverse source systems using SQL and cloud-based data technologies
- Identify, design, and implement process and infrastructure improvements, including automation of manual workflows, performance optimization, and scalability enhancements
- Partner with stakeholders across executive, product, data, analytics, and design teams to support data infrastructure needs and resolve data-related technical issues
- Perform root cause analysis on data quality, pipeline failures, and upstream/downstream dependencies to drive continuous improvement
- Develop and maintain processes for data transformation, metadata management, lineage, dependency tracking, and workload orchestration
- Optimize data delivery to ensure consistency, reliability, and performance across projects and platforms
- Support and collaborate with cross-functional teams in a fast-paced, evolving environment, providing technical leadership and data engineering best practices
Job Requirements:
- Cloud Platform: Microsoft Azure
- Data Engineering & ETL/ELT: Azure Data Factory, Databricks, Dell Boomi (or similar)
- Data Processing: SQL, Python, PySpark
- Databases & Storage: Relational SQL databases, Data Warehouses
- Data Architecture: Data Warehousing methodologies, Master Data Management, Data Vault 2.0
- Analytics & Integration: Enterprise data pipelines, large-scale data integration
- Version Control & Collaboration: Git, enterprise collaboration tools
Accessibility Statement:
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Our Commitment to Diversity, Equity, and Inclusion:
Signify’s mission is to empower every person, regardless of their background or?circumstances, with an equitable chance to achieve the careers?they deserve. Building a diverse future, one placement at a?time. Check out our DE&I page here