Senior DevOps Engineer

• About Us:

We are brand builders who focus our passion and creativity to build Calvin Klein and TOMMY HILFIGER into the most desirable lifestyle brands in the world and at the same time position PVH as of the best-performing brand groups in our sector. Guided by our values and enabled by our scale and global reach, we are driving fashion forward for good, as team with vision and plan. That’s the Power of Us, that’s the Power of PVH+.

One of PVH’s greatest strengths is our people. Our collective desire is to create a workplace environment where every individual is valued, and every voice is heard, and we are committed to fostering an inclusive and diverse community of associates with a strong sense of belonging. Learn more about Inclusion & Diversity at PVH

here

.

• POSITION SUMMARY:

We are looking for a Senior DevOps Engineer to join the Enterprise Data Platform team and help mature the engineering, automation, deployment, monitoring, and operational capabilities of our global data platform.

The Enterprise Data Platform is a strategic data foundation supporting analytics, reporting, data products, and business intelligence across multiple regions and business domains. The platform is moving toward a modern AWS-first data architecture, with Databricks, Delta Lake, Unity Catalog, AWS S3, IAM, KMS, PrivateLink, Terraform, GitLab CI/CD, and Databricks Asset Bundles as key technology components.

This role will be responsible for improving how EDP engineering teams build, test, deploy, monitor, and operate data platform solutions across environments. You will work closely with data engineers, architects, platform teams, security, cloud infrastructure, AMS support teams, and product stakeholders to create reliable, secure, automated, and scalable DevOps practices for EDP.

• PRIMARY RESPONSIBILITIES/ACCOUNTABILITIES OF THE JOB:

Area

Responsibilities

DevOps & CI/CD

Design, build, and maintain GitLab CI/CD pipelines for EDP data engineering assets, Databricks jobs, workflows, notebooks, SQL assets, and platform configurations.

Infrastructure as Code

Build, maintain, and improve Terraform modules for AWS infrastructure, Databricks workspace configuration, networking, IAM, storage, and platform components.

Databricks Deployment Automation

Implement and standardize Databricks Asset Bundles (DAB) for deploying Databricks workflows, jobs, notebooks, permissions, and environment-specific configurations.

AWS Platform Engineering

Support AWS-native platform components including S3, IAM roles, KMS, STS, VPCs, subnets, security groups, route tables, VPC endpoints, PrivateLink, and cross-account access patterns.

Release Management

Support structured release governance across Dev, QA, QA2, Prod, and DR environments, including release tagging, deployment validation, rollback planning, and production readiness checks.

Monitoring & Observability

Improve monitoring and alerting for Databricks jobs, workflows, pipelines, SQL warehouses, batch SLAs, cloud services, and platform health using Databricks system tables, cloud logs, dashboards, and alerts.

Security & Access Controls

Automate and govern least-privilege access using IAM roles, service principals, Unity Catalog permissions, storage access controls, secrets, KMS encryption, and audit logging.

Network & Connectivity

Support secure connectivity patterns involving Databricks on AWS, S3, PrivateLink, VPC endpoints, enterprise network inspection, DNS, controlled ingress/egress, and cross-cloud transition scenarios.

Operational Excellence

Partner with AMS and engineering teams to improve incident triage, root cause analysis, batch monitoring, SLA visibility, production support handoffs, and operational runbooks.

Engineering Standards

Help define and enforce standards for GitLab workflows, merge request checks, deployment approvals, unit testing, release validation, and reusable deployment patterns.

Platform Modernization

Contribute to EDP’s AWS migration and modernization roadmap, including platform automation, environment consistency, scalable deployment patterns, and improved operational resilience.

• SUPERVISORY RESPONSIBILITIES: Direct: NA

• BUDGETARY RESPONSIBILITIES:

None

Ø

• RESOURCEFULNESS:

• GitLab CI/CD pipeline design and implementation
• Terraform modules for AWS and Databricks infrastructure
• Databricks Asset Bundles for Databricks deployment automation
• Databricks workspace configuration and environment promotion
• Dev, QA, QA2, Prod, and DR deployment patterns
• AWS S3, IAM, KMS, STS, VPC endpoints, PrivateLink, and cross-account access
• Databricks Unity Catalog permissions and governance automation
• Databricks workflows, jobs, notebooks, SQL warehouses, and cluster policies
• Release tagging, deployment approvals, rollback procedures, and release validation
• Monitoring for Databricks jobs, workflows, batch SLAs, and platform usage
• Operational runbooks for AMS, platform support, and engineering teams
• Secure access patterns for data ingestion, data products, and enterprise integrations

• ENVIRONMENT:

Ø Complex work environment with heavy interpersonal & technical demands

Ø Requires multi-tasking and coordination across multiple geographic locations

• QUALIFICATIONS & EXPERIENCE:

• Bachelor’s degree or equivalent experience in Computer Science, Information Technology, Engineering, Data Engineering, or a related field.

6+ years of DevOps, platform engineering, cloud engineering, or data platform engineering experience

.

• Strong hands-on experience with

GitLab CI/CD

.

• Strong hands-on experience with

Terraform

for infrastructure automation.

• Experience with

AWS cloud infrastructure

, especially S3, IAM, KMS, STS, VPC, subnets, security groups, VPC endpoints, and PrivateLink.

• Experience with

Databricks platform engineering or deployment automation

.

• Experience implementing or supporting

Databricks Asset Bundles

, or similar Databricks deployment frameworks.

• Good understanding of

Databricks workflows, jobs, clusters, notebooks, SQL warehouses, permissions, and workspace configuration

.

• Good understanding of

Unity Catalog

, data access controls, external locations, storage credentials, and governance concepts.

• Strong scripting experience using

Python, Bash, or similar scripting languages

.

• Good understanding of

SQL, Spark, Delta Lake, and modern data platform concepts

.

• Experience supporting production platforms with monitoring, alerting, logging, incident management, and operational runbooks.
• Strong troubleshooting skills across cloud, network, security, CI/CD, and data platform layers.
• Experience working in Agile delivery models with globally distributed engineering teams.

Preferred Experience

Experience with or more of the following would be a strong plus:

• AWS multi-account patterns and cross-account IAM role access.
• AWS S3 data lake architecture, bucket policies, KMS encryption, and lifecycle policies.
• AWS PrivateLink, gateway endpoints, interface endpoints, DNS, and enterprise network routing.
• Databricks on AWS, including workspace deployment, cluster policies, job clusters, serverless, SQL warehouses, system tables, and audit logs.
• Databricks Unity Catalog, Delta Sharing, external locations, storage credentials, and permission automation.
• Databricks Asset Bundles for multi-environment deployment.
• GitLab merge request workflows, CI/CD templates, protected branches, environment approvals, and release tagging.
• Terraform module design, state management, environment parameterization, and reusable IaC patterns.
• Data platform observability using Databricks system tables, cloud logs, dashboards, and SLA reporting.
• Power BI connectivity to Databricks and service-principal-based access patterns.
• MLOps concepts including model deployment, versioning, feature stores, experiment tracking, and ML workflow automation.
• Experience supporting Azure-to-AWS migration or multi-cloud transition programs.

Key Skills

Skill Area

Expected Capability

Primary Cloud

AWS, S3, IAM, KMS, STS, VPC, PrivateLink, VPC endpoints

DevOps Platform

GitLab CI/CD, merge requests, protected branches, approvals, release tagging

Infrastructure as Code

Terraform modules, state management, reusable IaC patterns

Databricks Deployment

Databricks Asset Bundles, workflows, jobs, notebooks, SQL assets

Data Platform

Databricks, Delta Lake, Spark, Unity Catalog, SQL Warehouses

Security

IAM roles, service principals, KMS, secrets, access controls, auditability

Monitoring

Databricks system tables, cloud logs, dashboards, alerts, SLA tracking

Scripting

Python, Bash, SQL

Operations

Incident triage, RCA, runbooks, release controls, production support

Ways of Working

Agile delivery, documentation, cross-functional collaboration, ownership

You Are

• Proactive and comfortable owning platform improvements end to end.
• Strong in problem solving, debugging, and structured investigation.
• Experienced in building automation rather than relying on manual operations.
• Comfortable working across engineering, architecture, security, infrastructure, and support teams.
• Detail-oriented when it comes to production controls, access, security, and release quality.
• Pragmatic and delivery-focused, with a bias toward simplification and standardization.
• Able to explain technical topics clearly to both technical and non-technical stakeholders.
• Passionate about building reliable, scalable, secure, and well-governed data platforms.

Success in This Role Looks Like

• GitLab CI/CD becomes the standard deployment path for EDP engineering assets.
• Terraform modules are reusable, secure, and consistently applied across environments.
• Databricks Asset Bundles are adopted as the standard for Databricks job and workflow deployments.
• AWS infrastructure and Databricks environments are provisioned consistently and with minimal manual effort.
• Releases become safer, faster, and better governed across Dev, QA, QA2, Prod, and DR.
• Monitoring gives early visibility into job failures, SLA risks, platform issues, and operational bottlenecks.
• Security and access controls are automated, auditable, and aligned with least-privilege principles.
• AMS and engineering teams have clear runbooks, handoffs, and operational ownership models.

What We Offer

• Opportunity to work on a strategic global Enterprise Data Platform.
• Exposure to modern AWS-first data platform architecture with Databricks at the core.
• Opportunity to contribute to a major cloud migration and platform modernization journey.
• A collaborative, international technology environment.
• High visibility across data engineering, architecture, security, infrastructure, and analytics teams.
• Space to drive automation, improve engineering maturity, and shape DevOps standards for the platform.

PVH Corp. or its subsidiary ("PVH") is an equal opportunity employer and considers all applicants for employment on the basis of their individual capabilities and qualifications without regard to race, ethnicity, color, sex, gender identity or expression, age, religion, national origin, citizenship status, sexual orientation, genetic information, physical or mental disability, military status or any other characteristic protected under federal, state or local law. In addition to complying with all applicable laws, PVH is also committed to ensuring that all current and future PVH associates are compensated solely on job-related factors such as skill, ability, educational background, work quality, experience and potential.

• Bachelor’s degree or equivalent experience in Computer Science, Information Technology, Engineering, Data Engineering, or a related field.
• 6+ years of DevOps, platform engineering, cloud engineering, or data platform engineering experience.
• Strong hands-on experience with GitLab CI/CD.
• Strong hands-on experience with Terraform for infrastructure automation.
• Experience with AWS cloud infrastructure, especially S3, IAM, KMS, STS, VPC, subnets, security groups, VPC endpoints, and PrivateLink.
• Experience with Databricks platform engineering or deployment automation.
• Experience implementing or supporting Databricks Asset Bundles, or similar Databricks deployment frameworks.
• Good understanding of Databricks workflows, jobs, clusters, notebooks, SQL warehouses, permissions, and workspace configuration.
• Good understanding of Unity Catalog, data access controls, external locations, storage credentials, and governance concepts.
• Strong scripting experience using Python, Bash, or similar scripting languages.
• Good understanding of SQL, Spark, Delta Lake, and modern data platform concepts.
• Experience supporting production platforms with monitoring, alerting, logging, incident management, and operational runbooks.
• Strong troubleshooting skills across cloud, network, security, CI/CD, and data platform layers.
• Experience working in Agile delivery models with globally distributed engineering teams.