Quest Diagnostics

Data Engineer (Remote)

Quest Diagnostics Secaucus, New Jersey, United States

Medical and Diagnostic Laboratories · 10,001+ employees

12 h ago
Remote data-engineer Mid (2-5 yrs) Full-time United States
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About the role

You will design, develop, and deploy scalable data integration solutions and pipelines to support enterprise analytics and AI/ML initiatives. Additionally, you will act as a technical advisor to business customers while ensuring all data systems adhere to security and healthcare compliance standards.

What they look for

Data Engineering ETL Data Pipelines SQL Python Java Google BigQuery Snowflake Cloud Computing Data Modeling DevSecOps CI/CD GitHub Healthcare Analytics Data Governance Machine Learning

Requirements

Candidates must have 3-5 years of experience in data development, ETL processes, and cloud-based data warehousing. A bachelor's degree in a relevant field such as Computer Science or Engineering is required.

Full description

In this role, you will be responsible for designing, developing, testing, and deploying highly scalable, high performance data integration and transformation solutions in Quest’s enterprise data platform and the HAS data product. You will work with business customers to design large-scale data processing solutions, develop data pipelines optimized for scaling, and designing, building, and implementing data-driven systems to guide Quest’s reporting and analytics. This includes developing processes and solutions for mining, acquiring, transforming, standardizing, enhancing, migrating, verifying, and modeling Quest’s enterprise data. In addition, you will enable and assist advanced analytics initiatives that are building, training, deploying, and refining AI/ML models that efficiently analyze vast quantities of data to best serve our patient population.

Responsibilities

  • Act as a trusted technical advisor to business customers and internal teams, solving complex data challenges related to healthcare analytics.
  • Engineer and prepare both internal and customer-facing datasets, ensuring strict adherence to defined technical specifications, internal data standards, and external Statements of Work (SOWs).
  • Develop and maintain robust, scalable data pipelines to acquire, transform, and provision data for analytics and data science initiatives.
  • Design and build data models within cloud data warehouses (e.g., Google BigQuery, Snowflake) that are optimized for performance and scalability.
  • Collaborate with SD3 Data Scientists to productionize and manage the handoff of machine learning model inferences into our persistent data stores.
  • Partner with architecture and lead engineers to implement and adhere to modern DevSecOps standards, including CI/CD and version control using GitHub.
  • Ensure all data solutions are compliant with data governance, security policies, and healthcare regulations (e.g., HIPAA).
  • Contribute to organizational improvements in processes and technology by adopting new tools and best practices in data engineering.
  • Perform and support unit, integration, and performance testing to ensure that quality and reliability of data pipelines.

Qualifications

Required Work Experience:

  • 3-5 years of data development experience with a focus on building data pipelines and ETL processes
  • 3-5 years of experience with the cloud (AWS, Azure and/or Google Cloud Platform) – GCP experience highly preferred
  • 3-5 years of experience in cloud-based data warehouses (Snowflake, Google BigQuery, Amazon Redshift, Azure Synapse Analytics)
  • 3-5 years of experience with cloud-based ETL/ELT tools (Matillion, Glue, Data Factory). Matillion experience is strongly preferred.

• Bachelor’s Degree (Computer Science, Engineering, Information Systems, Mathematics, Business Analytics, or relevant degree)

Preferred Work Experience:

  • Experience with version control systems (Git)
  • Understanding of and willingness to embrace Agile Principles (Scrum)
  • Master’s Degree (Computer Science, Engineering, Information Systems, Mathematics, Business Analytics, or relevant degree)

Physical and Mental Requirements:

  • Open mindset, ability to quickly adapt new technologies and learn new practice

Knowledge:

  • Demonstrated knowledge of SQL, Java, Python, C/C++, Scala, Julia, and/or other modern data and analytics programming languages
  • Demonstrated knowledge of data modeling principles and database systems.
  • Familiarity with containerization technologies (e.g., Docker, Kubernetes) is a plus.
  • Demonstrated knowledge of operating systems (macOS, Microsoft Windows, Linux, Solaris and/or UNIX)

Skills:

  • Coding
  • Data Warehousing
  • Database schema optimization
  • Database Systems
  • Critical thinking skills
  • Business communication
  • ETL

Quest Diagnostics honors our service members and encourages veterans to apply.

While we appreciate and value our staffing partners, we do not accept unsolicited resumes from agencies. Quest will not be responsible for paying agency fees for any individual as to whom an agency has sent an unsolicited resume.

Equal Opportunity Employer: Race/Color/Sex/Sexual Orientation/Gender Identity/Religion/National Origin/Disability/Vets or any other legally protected status.

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