Staff Data Engineer - Science

Exact Sciences is dedicated to changing how the world prevents, detects, and guides treatment for cancer. The Staff Data Engineer will lead the design, development, and testing of complex software applications, ensuring high quality and accountability while collaborating with team members and stakeholders to enhance data analytics capabilities.

Responsibilities:

• Has in-depth understanding and works on a wide range of issues while applying advanced knowledge, skills, and practices to diverse programs and initiatives demonstrating creativity and mastery of specialized techniques, processes, procedures. Exercise independent judgment in methods, techniques, and evaluation criteria for obtaining results
• Troubleshoot issues and problems of high complexity for major software applications; break down complex tasks, alternatives, problems, and solutions with an eye on limiting the need for later problem solving; utilize mastery of tools needed to debug and diagnose issues in any type of environment
• Act as a Technical Lead for your team due to their trust in your technical expertise and coaching – lead without authority, show initiative and support all levels when needed without being asked; deliver feedback in a constructive manner; provide guidance to entry-level engineers; collaborate often with other technical leads, incorporating feedback as needed; focus team discussion on important aspects
• Design lasting applications while working with product teams. This may include organizing people and resources toward the effective and efficient purpose of pre-determined objectives serving large business or technology project(s)
• Take full ownership of quality and difficult designs that impact and influence the department’s delivery and approach
• Understand the scope and relationships of large features and productions for your domain
• Contribute, interpret, and communicate enterprise, technical, project, and operational strategies, taking into account company dynamics
• Build successful internal partnerships with peers, SMEs, stakeholders, and decision-makers. Manage vendor and external partnerships
• Consistently influence and make significant decisions across multiple projects. Guide discussions on critical areas of impact
• Ability to work nights and/or weekends, as needed
• Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork
• Support and comply with the company’s Quality Management System policies and procedures
• Maintain regular and reliable attendance
• Ability to act with an inclusion mindset and model these behaviors for the organization

Requirements:

• Bachelor's Degree in Data Science, Computer Science, Information Systems, Mathematics, or Engineering; or High School Diploma/General Education Degree and 12 years of relevant experience as outlined in the essential duties in lieu of Bachelor's Degree
• Spark on Snowflake or Databricks
• Python, Scala, SQL development
• ETL data pipelines
• Designing and implementing data modeling solutions using relational, dimensional, and/or NoSQL databases
• Database architecture testing methodology, including execution of test plans, debugging, and testing scripts and tools
• Multiple Big Data file formats (Parquet, Avro, Delta Lake)
• Cloud Infrastructure services (i.e., AWS, SQS, S3, and GitLab)
• Agile development tools; including, but not limited to, JIRA, Confluence repository
• RestAPI development
• Tableau, ideally including performance optimization
• Demonstrated ability to perform the essential duties of the position with or without accommodation
• Experience partnering with scientific research teams, such as biomarker discovery, computational biology, or clinical affairs
• Expertise in CI/CD best practices for data pipelines, including git-based workflows (Github/Gitlab), automated testing, and deployment strategies
• Advocate of test-driven development
• Experience integrating and processing real-world data (RWD), including electronic health records (EHR) and claims data, to support longitudinal patient analysis and clinical evidence generation
• Experience with data governance, security, and compliance best practices (RBAC, GDPR, HIPAA)