{"id":2446647,"url":"https://alion.io/job/qualys-directordbre","title":"Director,DBRE","company":{"id":18966,"name":"Qualys","domain":"qualys.com","url":"https://alion.io/company/qualys","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":50000,"max_usd":131000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":37},"experience_years_min":15,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Anthropic","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Cassandra","optional":false},{"name":"CI/CD","optional":false},{"name":"Datadog","optional":false},{"name":"Gemini","optional":false},{"name":"Grafana","optional":false},{"name":"Hadoop","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenSearch","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Oracle","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Qualys Cloud Platform","optional":false},{"name":"Redis","optional":false},{"name":"Self-Healing","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Tool Use","optional":false}],"status":"live","first_seen_at":"2026-10-13T13:46:00Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-13T13:46:00Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!\nThe Opportunity\nQualys runs one of the largest and most complex data platforms in the enterprise security industry - a massive Oracle and Exadata estate at the core, surrounded by a self-managed open-source big data fabric: Kafka, Hadoop, Cassandra, OpenSearch, Redis, Ceph, and Kubernetes. These systems directly underpin the product SLAs we deliver to 10,000+ customers worldwide.\nWe are looking for a Director of Database Reliability Engineering who combines deep technical craft with the leadership instinct to scale a team and the builder's mindset to ship systems that eliminate toil. You don't have to be the world's leading expert in every technology on the stack - but you must carry genuine depth in Oracle or large-scale distributed data systems, with strong working knowledge across the broader ecosystem, and the intellectual range to go deep where the situation demands it. We do not expect day-one mastery across every system; we expect depth in core areas and the proven ability to rapidly develop expertise where the platform needs it.\nThis role directly owns database platform operations and reliability practices, and influences adjacent infrastructure and application teams through technical credibility and cross-functional partnership. You will lead a team of ~30, serve as the final technical escalation point for the data platform, and shape the multi-year strategy for how Qualys builds, automates, and evolves its data infrastructure.\nCore Focus Areas\nThis is a wide-scope role. Here is how candidates should prioritize their self-evaluation:\n01Oracle + Distributed Systems Technical Depth - Deep in one, strong across the other - enough to lead architecture and hold the team accountable\n02Data Platform Reliability & Incident Ownership - SLOs, escalation authority, DR, predictive capacity - the foundational mandate\n03AI-Driven Automation & Toil Elimination - Building and shipping agents, not just evaluating tools - measurable impact on MTTR and operational load\n04Team Leadership & Org Development - Managing ~30 across ICs and managers; building culture, career ladders, and hiring bar\n05Vendor Management & Cost Optimization - Oracle relationship, licensing discipline, and infrastructure cost efficiency\nWhat Makes This Role Unique\n→Breadth of scope, depth of ownership - You hold the charter for Oracle/Exadata AND the full open-source big data stack - accountable for reliability across all of it\n→Build AI systems, not just use them - We expect shipped production tooling - AI agents, autonomous remediation, intelligent observability - not proof-of-concept demos\n→Strategy and execution in equal measure - You will define the multi-year data platform roadmap and then make it happen - this is not a pure operations role\n→Real cross-functional influence - Data reliability touches every product team; this role earns authority through technical credibility, not org chart position\n→A platform worth modernizing - Battle-tested at scale, with genuine complexity - and a leadership team committed to doing it right\nWhat You Will Build\nBeyond running the platform, we expect this leader to leave a concrete engineering footprint. Examples of the systems we want this role to build and own:\nAI-assisted incident triage system - LLM-powered log analysis and alert summarization that cuts triage time from minutes to seconds\nAutonomous remediation agents - Self-healing workflows for common failure patterns - space exhaustion, replication lag, lock contention, consumer group lag - with safe human escalation fallback\nNatural-language operational query interface - Engineers ask questions in plain English; the system queries metrics, logs, and configuration state to answer\nPredictive capacity and anomaly models - ML-driven forecasting for Oracle tablespace growth, Kafka partition pressure, and Cassandra compaction backlog\n Reliability-as-code pipeline gates - Automated schema review, load test, and regression detection integrated into CI/CD so reliability issues are caught before production\nWhat You Will Do\nOwn the Data Platform Reliability Charter\nDefine and drive SLOs, SLIs, and error budgets across Oracle, Exadata, Kafka, Cassandra, Hadoop, OpenSearch, Redis, Ceph, and Kubernetes-hosted data services\nServe as the final technical escalation point for all P0/P1 incidents; lead blameless post-incident reviews and drive permanent resolution - not workarounds\nOwn disaster recovery architecture, backup integrity standards, and data durability SLAs - validated through regular DR exercises\nEstablish predictive capacity planning and performance baselines across the full data platform footprint\nDrive cost efficiency and infrastructure utilization optimization - right-sizing resources, eliminating idle capacity, and building chargeback/showback visibility for leadership\nDefine and Execute the Multi-Year Data Platform Strategy\nDevelop and own a multi-year DBRE roadmap - covering reliability targets, modernization priorities, platform consolidation opportunities, and AI automation milestones\nDrive platform evolution decisions: when to standardize, when to consolidate, when to retire, and when to invest in new capabilities\nProvide architectural guidance for major data platform initiatives - schema design, topology changes, new technology adoption, and migration planning\nPartner with Product Engineering, Security, and Infrastructure leadership to embed reliability and cost constraints into platform direction from day one\nGo Deep on Oracle and Exadata\nCarry deep technical authority for Oracle Database (19c+), RAC, Data Guard, RMAN, and Exadata - sufficient to lead architecture reviews, diagnose production incidents, and hold senior engineers accountable\nDrive query optimization, AWR/ASH-based diagnostics, execution plan analysis, and schema design reviews for mission-critical OLTP and analytical workloads\nManage Oracle vendor relationships with technical and commercial depth: negotiate support contracts, challenge licensing interpretations, escalate through Oracle's senior channels, and ensure Qualys negotiates from a position of knowledge\nOwn Oracle licensing compliance end-to-end - a material financial and risk area requiring both engineering precision and commercial acumen\nLead Exadata patching cadence, storage cell failure playbooks, IORM policy tuning, and hardware lifecycle planning\nLead the Open-Source Big Data Platform\nArchitect and operate Kafka, Cassandra, Hadoop, OpenSearch, Redis, and Ceph deployments - self-managed at scale, not cloud-managed services\nApply strong distributed systems fundamentals - consensus and replication models, storage I/O patterns, network latency sensitivity, and horizontal scaling - to architectural decisions that hold under load\nPartner with DevOps and Platform Engineering on Kubernetes-native stateful workloads: operators, persistent volumes, storage class optimization, and capacity planning\nDrive standardization of runbooks, alerting, and operational playbooks across all technologies - documented, automated, no tribal knowledge\nBuild AI-Powered Reliability Systems\nDesign and ship AI agents that automate tier-1 database operational toil - systems running in production with measurable impact on MTTR and alert noise\nIntegrate LLM APIs (Anthropic, OpenAI, Gemini) into operational workflows for log triage, incident summarization, runbook execution, and anomaly-triggered decision support\nEvaluate AIOps platforms and observability tooling with engineering rigor - quantify the actual value, not the vendor pitch\nEmbed reliability-by-design upstream: schema review gates, load test automation, and database performance regression detection in CI/CD pipelines\nLead and Develop the DBRE Team\nManage, mentor, and develop ~30 DBAs, SREs, and data platform engineers across individual contributors and engineering managers\nDefine hiring standards, career ladders, and team structure that attract and retain senior database and reliability talent\nBuild a culture of technical rigor, blameless learning, and relentless automation - where manual toil is a bug, not a process\nEliminate single points of knowledge failure through documentation, cross-training, and disciplined on-call rotation design\nOwn workforce planning: headcount forecasting, skills gap analysis, and building specialist sub-teams as the platform evolves\nHow We Measure Success\n→Platform Availability - SLO attainment across all data services - reduction in unplanned production incidents attributable to DBRE gaps\n→MTTA / MTTR - Measurable improvement in time to detect and resolve incidents, accelerated by AI tooling\n→Automation Coverage - Percentage of tier-1 operational tasks eliminated through shipped agents and tooling\n→Cost Efficiency - Infrastructure utilization rates, Oracle licensing optimization, and idle/over-provisioned resource reduction\n→Team Health & Retention - On-call load reduction, career growth trajectory, and senior IC/manager retention\n→ Platform Strategy Execution - Multi-year roadmap milestones delivered; capacity forecasts validated against actual growth\nWhat We Are Looking For\nMust Have\n15+ years in database engineering, reliability engineering, or data platform operations - with 5+ years leading multi-person teams including at least one layer of managers\nDeep expertise in Oracle or large-scale distributed data systems, with strong working knowledge across the broader ecosystem (Kafka, Cassandra, Hadoop, OpenSearch, Redis, Ceph, Kubernetes)\nStrong distributed systems fundamentals - replication and consensus models, storage I/O, network latency tradeoffs, and scaling patterns for stateful workloads - applied to real production decisions\nShipped operational tooling or agents using LLM APIs with measurable impact (MTTR reduction, toil elimination, alert noise reduction) - production systems, not proofs of concept\nOracle vendor relationship management - commercial negotiation, license compliance ownership, and technical escalation through Oracle's support and sales organizations\nInfrastructure cost control - hands-on experience right-sizing compute and storage, eliminating idle capacity, and building cost visibility (chargeback/showback) across database infrastructure\nTrack record leading teams of 15+ engineers with both IC and manager-level reports; experience growing technical talent and building hiring bars\nExecutive communication skills - translating database risk, reliability posture, and investment needs to C-suite audiences with clarity and commercial grounding\nExperience serving as final escalation point for production data platform incidents - with the technical depth to diagnose, direct, and close\nStrong Plus\nExadata-specific depth: IORM policy tuning, smart scan diagnostics, storage server failure recovery, and hardware lifecycle decision-making\nKubernetes-native data platform experience with stateful workload operators (Strimzi, Cassandra Operator, OpenSearch Operator, Redis Operator)\nExperience with AIOps or observability platforms (Datadog, Grafana, OpenTelemetry) including custom exporter and agent development\nFamiliarity with agentic integration patterns (MCP, tool-use APIs) for building AI-augmented operational toolchains\nHands-on coding in Python, Go, or shell scripting - enough to design and ship internal tooling independently\nBackground in security or compliance-adjacent industries where data integrity and auditability carry regulatory weight\nWho This Role Is For\nThis role is for a data platform leader who still gets pulled in by a gnarly execution plan, and who sees a recurring on-call alert as a signal that something needs to be built - then builds it. You lead by doing as much as by directing, and your team follows you because they know you have sat in their chair.\nYou hold Oracle's feet to the fire in a negotiation and hold your engineers to a high bar in a design review. 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