We are looking for a DevOps / Platform Lead to provide technical direction, mentorship, and escalation ownership across our DevOps and Platform Engineering practice. This is a technical leadership role with hands-on depth — combining architecture guidance, vendor management, and engineering oversight for the DevOps and Platform Engineer group supporting the enterprise Data Platform, ingestion, orchestration, CI/CD, and observability layers. Leads a team of Platform and DevOps Engineers. You own the health, roadmap, and delivery of the platform practice. 

Key Responsibilities: 

Technical Strategy & Architecture 

• Set the technical direction for DevOps and Platform Engineering — CI/CD standards, IaC patterns, orchestration, and observability. 

• Own the architecture roadmap for the ingestion layer, scheduling, and deployment automation. 

• Guide the team on modern Databricks-native operating patterns. 

Platform Operations & Reliability 

• Serve as the single technical escalation point for DevOps and Platform incidents and change management. 

• Drive problem management practices — reduce recurring incidents and champion permanent fixes over reactive support. 

• Ensure operational readiness for year-end activities, compliance, and audit requirements. 

• Track platform KPIs — reliability, incident volume, deployment success rate, and cost efficiency. 

Automation & Continuous Improvement 

• Champion automation and agentic operations to reduce manual effort and improve reliability. 

• Drive continuous improvement in ways of working, aligned with industry-standard operating maturity models. 

Leadership & Mentorship 

• Mentor and grow Platform and DevOps Engineers on best practices, code quality, and career growth. 

• Shape team capacity and capability — hiring input, skills development, and workload planning across the Platform/DevOps group. 

• Represent the DevOps / Platform practice in Data & AI leadership forums and cross-functional reviews. 

Stakeholder & Vendor Management 

• Partner with Data Engineering leadership to align platform capabilities with data delivery needs. 

• Own vendor coordination with Databricks and adjacent platform vendors — case management, upgrade planning, and license/capacity discussions. 

What Success Looks Like (First 6–12 Months):  

• You'll establish the platform's CI/CD and observability standards, reduce recurring incidents through problem management, mature vendor and upgrade governance, and lift the team's automation and AI-native operating maturity. 

Required Qualifications: 

• Bachelor's or Master's degree in Computer Science, Information Technology, or equivalent relevant experience. 

• 10+ years of overall experience in Data Engineering, Platform Engineering, or DevOps including 2+ years in a technical lead capacity. 

• Strong hands-on background in Databricks, cloud platforms, CI/CD, and Infrastructure-as-Code. 

• Prior experience leading platform or DevOps teams supporting enterprise data workloads. 

• Proven experience managing vendor relationships and complex upgrade programs. 

• Excellent communication and stakeholder management skills across engineering and business audiences. 

Preferred Qualifications: 

• Familiarity with Unity Catalog governance and Databricks-native AI capabilities. 

• Exposure to industry-standard maturity models for data and platform operations. 

• Databricks Certified Data Engineer Professional or Cloud Solutions Architect Professional certification. 

Competencies: 

• Ownership and accountability — end-to-end responsibility for platform health and delivery. 

• Servant leadership — grows the team while removing blockers. 

• Strategic thinking — balances short-term operational stability with long-term platform evolution. 

• Diplomatic and clear communicator — comfortable with vendors, leadership, and engineering peers. 

• Bias for automation, KPIs, and outcome-driven service delivery.