Senior Data Engineer: Lead Enterprise Pipelines & AI/ML

Quest Diagnostics; Secaucus (NJ); On-site; USD 140,000 - 180,000; Full time

Job summary

Quest Diagnostics is seeking a senior data engineer to lead design, development, testing, and deployment of scalable data integration and transformation solutions across our enterprise data platform and HAS data product.

You will partner with architects, business customers, and cross-functional teams to shape data architecture strategy, design large-scale processing solutions, and build data-driven systems for reporting and analytics.

Qualifications

• 5-8 years of data development experience focusing on building data pipelines and ETL processes.
• 5-8 years of cloud experience (AWS, Azure and/or Google Cloud) – GCP preferred.
• 5-8 years of cloud-based data warehouses (Snowflake, BigQuery, Redshift, Azure Synapse).
• 5-8 years of cloud-based ETL/ELT tools (Matillion, Glue, Data Factory).
• 2+ years in a technical lead or data/solution architecture capacity.

Responsibilities

• Serve as senior advisor to business customers, architects, and teams to solve complex data challenges in healthcare analytics.
• Lead the design and architecture of end-to-end data solutions and translate requirements into scalable designs.
• Define and govern data architecture standards, patterns, and best practices across data engineering.
• Architect, develop, and optimize robust, scalable data pipelines for analytics and data science.
• Lead handoff of ML model inferences into persistent data stores and productionize models.
• Champion DevSecOps standards including CI/CD, automated testing, and GitHub version control.

Skills

SQL

Java

Python

C/C++

Scala

Data modeling

Data warehousing

ETL

CI/CD

Mentoring

Education

Bachelor’s Degree

Master’s Degree

Tools

Matillion

AWS Glue

Azure Data Factory

Snowflake

BigQuery

Redshift

Git

Docker

Kubernetes

Job description

Quest Diagnostics is seeking a senior data engineer to lead design, development, testing, and deployment of scalable data integration and transformation solutions across our enterprise data platform and HAS data product.

You will partner with architects, business customers, and cross-functional teams to shape data architecture strategy, design large-scale processing solutions, and build data-driven systems for reporting and analytics.