Platform Engineer III

Atlantic Health SystemMorristown, NJ

About The Position

As a Data Platform Engineer III (Senior), you will design, build, and operate the foundational infrastructure that powers data-driven decisions across the organization. You will own complex technical problems end-to-end — from architecture and implementation to operations and reliability — while mentoring junior engineers and influencing cross-team technical strategy. You will collaborate closely with analytics, machine learning, and product teams to evolve the platform to meet growing scale, compliance, and quality requirements. This is a high-impact, high-autonomy role for engineers who care deeply about data reliability, developer experience, and scalable system design.

Requirements

  • Design and implement scalable, reliable, and cost-efficient data platform components, including ingestion pipelines, storage layers, orchestration frameworks, and serving infrastructure.
  • Lead architectural decisions for data systems, evaluate trade-offs, and document technical decisions (ADRs) for broader team alignment.
  • Own the full lifecycle of platform components: design, build, test, deploy, monitor, and optimize.
  • Drive adoption of platform-as-a-product principles, ensuring internal teams have self-service tooling, clear SLAs, and well-documented APIs.
  • Implement and maintain data observability tooling (data quality checks, anomaly detection, lineage tracking) to ensure trust in data assets.
  • Define and enforce SLAs/SLOs for data pipelines and platform services; own incident response and root-cause analysis for platform-related outages.
  • Establish and improve testing practices for data pipelines (unit, integration, and contract testing).
  • Manage cloud data infrastructure (AWS, GCP, or Azure) using infrastructure-as-code tools such as Terraform, Pulumi, or CDK.
  • Optimize platform cost, performance, and scalability through profiling, benchmarking, and capacity planning.
  • Build and maintain CI/CD pipelines for data platform components; enforce engineering best practices (code review, versioning, documentation).
  • Serve as a technical anchor for platform squads; mentor Level I and II engineers through code reviews, pairing sessions, and design feedback.
  • Partner with data engineering, ML engineering, and analytics teams to understand requirements and translate them into platform capabilities.
  • Represent the data platform team in cross-functional planning; contribute to roadmap prioritization and estimation.
  • Contribute to and help maintain internal engineering standards, runbooks, and on-call practices.

Responsibilities

  • Design and implement scalable, reliable, and cost-efficient data platform components, including ingestion pipelines, storage layers, orchestration frameworks, and serving infrastructure.
  • Lead architectural decisions for data systems, evaluate trade-offs, and document technical decisions (ADRs) for broader team alignment.
  • Own the full lifecycle of platform components: design, build, test, deploy, monitor, and optimize.
  • Drive adoption of platform-as-a-product principles, ensuring internal teams have self-service tooling, clear SLAs, and well-documented APIs.
  • Implement and maintain data observability tooling (data quality checks, anomaly detection, lineage tracking) to ensure trust in data assets.
  • Define and enforce SLAs/SLOs for data pipelines and platform services; own incident response and root-cause analysis for platform-related outages.
  • Establish and improve testing practices for data pipelines (unit, integration, and contract testing).
  • Manage cloud data infrastructure (AWS, GCP, or Azure) using infrastructure-as-code tools such as Terraform, Pulumi, or CDK.
  • Optimize platform cost, performance, and scalability through profiling, benchmarking, and capacity planning.
  • Build and maintain CI/CD pipelines for data platform components; enforce engineering best practices (code review, versioning, documentation).
  • Serve as a technical anchor for platform squads; mentor Level I and II engineers through code reviews, pairing sessions, and design feedback.
  • Partner with data engineering, ML engineering, and analytics teams to understand requirements and translate them into platform capabilities.
  • Represent the data platform team in cross-functional planning; contribute to roadmap prioritization and estimation.
  • Contribute to and help maintain internal engineering standards, runbooks, and on-call practices.

Benefits

  • Medical, Dental, Vision, Prescription Coverage (22.5 hours per week or above for full-time and part-time team members)
  • Life & AD&D Insurance.
  • Short-Term and Long-Term Disability (with options to supplement)
  • 403(b) Retirement Plan: Employer match, additional non-elective contribution
  • PTO & Paid Sick Leave
  • Tuition Assistance, Advancement & Academic Advising
  • Parental, Adoption, Surrogacy Leave
  • Backup and On-Site Childcare
  • Well-Being Rewards
  • Employee Assistance Program (EAP)
  • Fertility Benefits, Healthy Pregnancy Program
  • Flexible Spending & Commuter Accounts
  • Pet, Home & Auto, Identity Theft and Legal Insurance
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