GDP Test Engineer

Digital Health Technology team powers digital experiences and engagement to enhance the lives of millions of people every day through connected care. We build, deliver and manage a portfolio of data management platforms and mobile offerings in support of our core businesses. We thrive on simple and elegant architecture and agility. You'll be immersed in a dynamic high-growth environment and empowered to excel, take informed risks, and drive ingenuity across the enterprise.

The primary role of the Test Engineering function within the Global Data Platform (GDP) Quality team is to work alongside data engineers in executing proper testing to specifications and designs for new products or improvements and enhancements to existing products. GDP data integrations and pipelines support production machine learning models, analytics, and core product/enterprise features. It is imperative that data provided GDP that is utilized in Software as a Medical Device ( SaMD ) products meets the appropriate quality requirement s .

Test Engineers work closely with developers, data scientists, product owners, quality engineers, product teams, and potential downstream customers to understand and define appropriate test coverage to defined system requirements and designs . Test E ngineers must execute sufficient medical-device level tests and test coverage for traceability to all requirements and must do so through as much automation as possible . Test engineers will also work on continuous improvement activities to ensure the data platform follows state-of-the-art data quality processes .

Let's talk about Responsibilities

Testing :

• Work c losely with engineers , data scientists, and product owners to craft and develop automated test plans
• Monitor and improve coverage of tests within the CI/CD loop to adequately test executed projects
• Document necessary quality records such as test plans, reports, release documentation, and traceability records
• Identify, record, track, and reproduce reported bugs either from internal development and/ or reported by external customers

Continuous Improvement :

• The primary objective of Test Engineering specialization is to test, verify, and validat e implemented data processing systems
• Key responsibilities include implementing data continuous integration tests verifying data quality between source and destination systems
• Create a methodology for the validation of developed testing
• Work closely with development teams to determine appropriate scope and length of testing plans , and customers to identify potential issues that may require additional mitigations

• Contribute to the automation and further refinement of tests in machine learning model development and deployment
• Act as a subject matter expert in informing monitoring KPIs with respect to data quality metrics
• Build out observability around our test coverage and data quality KPIs
• Identify potential process issues and help implement continuous improvement changes to the supporting data quality system
• Be able to c learly articulate and communicate issues, including root cause analysis, scales of impact, and potential solutions to necessary stakeholders

• Perform work in a specialized area of expertise that requires knowledge of fundamental themes, principles, and concepts. Typically requires a university degree or equivalent work experience
• Build stable working relationships internally to exchange information
• Receive instruction, guidance, and direction from others

Let's talk about Qualifications and Experience

Required:

• Bachelor's degree
• Minimum of 3 years of related experience in functional and integration testing
• Follows standard practices and procedures , has a core understanding of quality system frameworks such as ISO 9001 or ISO 13485

• Understand s essential data quality and privacy requirements and regulations
• Minimum knowledge in SQL, noSQL databases
• Understanding of CI/CD processes
• Python
• Snowflake

• Terraform

Bonus Points :

• Experience with JIRA or equivalent dev tracking systems, familiarity with integrated test management tools such as TestRails a plus
• Familiarity with ETL validation methodologies and solutions

• Experience with DBT
• Understanding of design and development methodologies of machine learning models
• Fundamental understanding of data lakes and serverless ETL (S3/Spark/Glue)
• Experience and/or familiarity in technologies like AWS Glue, Terraform, Py S park , Snowflake, AWS EMR, Apache Airflow, AWS S3, Kafka
• Applies functional knowledge and existing methodologies to solve complex problems or execute specialized projects

• Exercises judgment in selecting methods, techniques, and evaluation criteria for obtaining results

Joining us is more than saying "yes" to making the world a healthier place. It's discovering a career that's challenging, supportive and inspiring. Where a culture driven by excellence helps you not only meet your goals, but also create new ones. We focus on creating a diverse and inclusive culture, encouraging individual expression in the workplace and thrive on the innovative ideas this generates. If this sounds like the workplace for you, apply now!