Senior Cloud Engineer

Salary: $155,000 - 195,000 per year Requirements:

• We require at least 3 years of experience in cloud operations, DevOps, or systems administration.
• We require at least 3 years of experience in data management, data quality, data governance, or data engineering within a production analytics environment.
• We need hands-on experience designing and implementing data quality controls across ingestion, transformation, and reporting layers.
• We require experience defining and operationalizing data governance standards, including ownership models, business definitions, and critical data elements.
• We require at least 2 years of hands-on experience with a major cloud platform such as AWS, Azure, or Google Cloud Platform.
• We need experience deploying and supporting production infrastructure in cloud environments.
• We look for a proven record of delivering highly available, scalable systems.
• We require experience with infrastructure as code and automation tools.
• We need experience supporting data platforms or analytics workloads.
• We prefer a background in healthcare, life sciences, or other regulated industries with compliance requirements.
• We value 5+ years of cloud operations or DevOps experience.
• We prefer multi-cloud experience across AWS, Azure, and/or Google Cloud Platform.
• We prefer experience with containerization and orchestration technologies such as Docker, Kubernetes, or ECS.
• We prefer experience supporting Snowflake, Redshift, BigQuery, or similar cloud data warehouses.
• We prefer familiarity with observability platforms such as Datadog, New Relic, or Splunk.
• We prefer prior healthcare experience with HIPAA compliance.
• We prefer experience with data pipeline orchestration tools such as Airflow, dbt, or Prefect.
• We prefer experience implementing automated data quality monitoring tools, including rule engines, pipeline validation, or anomaly detection.
• We prefer experience building and maintaining data dictionaries, metadata repositories, and lineage documentation.
• We prefer experience supporting AI/ML or advanced analytics use cases that demand strong data accuracy and consistency.
• We require a bachelors degree in computer science, information technology, engineering, or a related technical field, or equivalent work experience.
• We prefer a masters degree in computer science, information technology, or a related field.
• We prefer cloud certifications such as AWS Solutions Architect, Azure Administrator, Google Cloud Professional, DevOps or infrastructure certifications, ITIL Foundation, or security certifications such as Security+ or CISSP.

• We deploy, configure, and maintain cloud infrastructure across AWS, Azure, or Google Cloud Platform.
• We manage compute, storage, networking, and security components.
• We implement and sustain infrastructure as code using tools such as Terraform, CloudFormation, or ARM templates.
• We optimize cloud utilization and drive cost-efficiency initiatives.
• We maintain clear documentation for architecture, configurations, and operational procedures.
• We implement and support monitoring for infrastructure, applications, and data pipelines.
• We configure alerts and dashboards using tools such as CloudWatch, Azure Monitor, Datadog, or similar platforms.
• We coordinate incident response with cross-functional teams and help resolve outages and performance issues.
• We develop and maintain automation scripts using Python, PowerShell, or Bash.
• We build and support CI/CD pipelines for infrastructure deployments and application releases.
• We automate routine operations to improve efficiency and reduce manual work.
• We implement and maintain cloud security controls and data platform protections in line with our policies.
• We ensure alignment with HIPAA, HITRUST, SOC 2, and other regulatory obligations.
• We maintain audit logs and support compliance reporting activities.
• We work with security and compliance teams during assessments and audits.
• We support data platform infrastructure, including data warehouses, data lakes, and ETL systems.
• We monitor data pipeline performance and troubleshoot processing problems.
• We manage our data quality framework, including quality rules, monitoring standards, and issue-resolution processes.
• We implement automated data validation and monitoring controls across ingestion, transformation, and delivery pipelines.
• We partner with data platform leadership to define and develop data quality KPI reporting.
• We implement data retention and archival policies.
• We manage database systems and backup/recovery procedures.
• We optimize query performance and resource allocation for analytical workloads.
• We coordinate with data engineering teams on platform upgrades and maintenance.
• We monitor performance metrics and identify opportunities for optimization.
• We conduct capacity planning and scaling activities.
• We reduce infrastructure costs through rightsizing, reserved instances, and resource cleanup.
• We collaborate with data engineering, analytics, and development teams on infrastructure needs.
• We provide technical guidance and support for cloud infrastructure questions.
• We work with vendors and cloud providers to resolve technical issues.
• We support deployments and release coordination.
• We create and maintain technical documentation and knowledge base articles.
• We train team members on cloud operations procedures and best practices.

• AI
• Airflow
• ARM
• AWS
• Redshift
• Architect
• Azure
• BigQuery
• Bash
• CI/CD
• Cloud
• CloudWatch
• Datadog
• DevOps
• Docker
• ETL
• Support
• ITIL
• Kubernetes
• PowerShell
• Python
• Security
• Snowflake
• Splunk
• Terraform
• dbt
• Lambda
• Data Warehouse
• EC2
• Git
• GitHub
• GitLab
• IAM
• Incident Management
• Jenkins
• Product Manager
• Pulumi
• SQL

More:

We are Quest Diagnostics, and we support Health Analytics Solutions (HAS) through reliable, secure cloud infrastructure and strong data operations. Our Cloud Operations and Data Quality Engineer role plays a key part in keeping our platforms highly available, efficient, and compliant while also establishing a data management and quality framework for our HAS data product. We work closely with data engineering, analytics, development, security, and compliance teams to support production workloads and scalable analytics solutions. We value veterans and are an equal opportunity employer.

last updated 33 week of 2026