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.
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