About the role

DevOps / Platform Lead

10+ yrs (2+ yrs tech lead)

Databricks · CI/CD · IaC (hands-on) · led platform/DevOps teams · technical team management & upgrade program mgmt · exec communication

Unity Catalog governance · Databricks-native AI · maturity models · Databricks Professional / Cloud Architect Professional cert

No prior platform/DevOps team-lead experience = reject

Platform Lead:

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.