{"id":176171,"url":"https://alion.io/job/skan-ai-senior-database-administrator","title":"Senior Database Administrator","company":{"id":63247,"name":"Skan AI","domain":"skan.ai","url":"https://alion.io/company/skan-ai","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":{"grade":"A","score":90,"open_postings":10,"ghost_share":0,"stale_share":0.2,"repost_share":0,"time_to_fill_p50_days":81,"computed_at":"2026-10-20T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":37000,"max_usd":75000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":71},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Platform Engineering","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Ansible","optional":true},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-08-04T20:06:58Z","employer_posted_date":"2026-08-04","last_verified_at":"2026-10-20T10:11:04Z","board_verified":true,"closed_at":null,"days_open":76,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":76},"description":"Be at the Forefront of the Agentic AI Revolution\nAt Skan AI, you'll be part of the team pioneering the context engine for human and agentic execution, bringing context from enterprise operators, systems, and processes to power how the world's largest organizations execute their most complex, mission-critical work.\nWhy Join Skan AI\nWe're in hyper-growth mode at exactly the right moment in history. As enterprises race to adopt agentic AI, we're uniquely positioned to deliver the clear signal they desperately need: a platform that trains and grounds AI Agents in trillions of real execution signals, enabling reliable, compliant automation of their most complex processes.\nBacked by Dell Technologies Capital and other leading investors, we're the only company that can bridge the gap between AI's promise and enterprise reality, making us perfectly positioned to define the agentic era for modern enterprises.\nOur diverse, collaborative team of 250+ innovators is solving category-defining challenges at the intersection of AI, process intelligence, and enterprise work. Diverse perspectives fuel breakthrough thinking, cross-functional collaboration is the norm, and our work directly transforms how Fortune 500 companies operate. We are shaping the future of work itself.\nPosition Summary\nWe are seeking a Senior Database Administrator (DBA) with deep, hands-on expertise across PostgreSQL, MongoDB, and Databricks to own the health, performance, scalability, and reliability of our large-scale data environments. This is a highly technical role for someone who thrives on operating databases at very high data volumes and who takes pride in building systems that are fast, resilient, and cost-efficient.\nThe primary focus of this role is administration and platform engineering: configuring, setting up, and continuously optimizing database platforms; instrumenting comprehensive monitoring and metrics; right-sizing environments in response to changing demand; and standing up schemas and configurations aligned to evolving requirements. As a secondary but important focus, the role supports data analysis activities, troubleshoots production data issues, plans capacity, performs maintenance, and takes proactive action to prevent outages before they occur.\nThe ideal candidate is technically outstanding across all three platforms, highly collaborative, and genuinely eager to learn and grow as our data estate and technology stack evolve.\nPrimary Responsibilities - Database Administration & Platform Engineering\nConfiguration, Setup & Optimization\nProvision and configure PostgreSQL, MongoDB, and Databricks environments from the ground up, applying tuned parameters, storage layouts, and connection strategies appropriate to very large data volumes.\nOptimize database configuration on an ongoing basis - memory, buffers, connection pooling, indexing strategy, partitioning/sharding, vacuum/compaction, query planning, and workload isolation - to sustain performance as volumes grow.\nStand up schemas and configurations based on functional and non-functional requirements gathered from engineering, analytics, and product stakeholders, balancing normalization, access patterns, and performance.\n Manage Databricks clusters, workspaces, and compute policies, tuning Spark configurations, autoscaling behavior, and storage (Delta Lake) layouts for efficient processing of very large datasets.\nMonitoring, Metrics & Observability\nDesign and implement monitoring across all three platforms - throughput, latency, query performance, replication lag, lock contention, storage utilization, and resource saturation.\nEstablish meaningful metrics, dashboards, and alerting thresholds that surface issues early and drive proactive intervention rather than reactive firefighting.\nDefine and track service-level objectives (SLOs) and key operational indicators, and report on the health and performance of the data estate.\nElastic Scaling & Capacity Management\nResize and scale environments - vertically and horizontally - based on real-time and forecasted demand, ensuring performance during peaks while controlling cost during troughs.\nImplement and tune autoscaling, sharding, replication, and partitioning strategies to accommodate sustained growth in data volume and concurrency.\nContinuously evaluate cost-to-performance trade-offs across cloud storage and compute tiers.\nSecondary Responsibilities - Operations, Reliability & Analysis Support\nProduction Troubleshooting & Proactive Reliability\nTroubleshoot and resolve production data issues, including slow queries, data anomalies, replication problems, contention, and platform incidents - often under time pressure.\nMonitor for performance degradation and take proactive action to prevent outages before they impact users, based on data-driven signals and early warning indicators.\nParticipate in incident response and on-call rotations, conduct root-cause analysis, and drive durable fixes and preventative measures.\nCapacity Planning & Maintenance\nPlan for capacity upgrades, forecasting growth in storage, compute, and I/O, and scheduling upgrades ahead of demand.\nPerform routine and preventative maintenance - patching, version upgrades, index maintenance, vacuum/compaction, backup verification, and configuration hygiene - with minimal disruption.\nMaintain runbooks, operational documentation, and disaster-recovery procedures.\nData Analysis Support\nSupport data analysis activities by assisting analysts and engineers with query optimization, data access, and structuring data for efficient analytical workloads.\nPartner with analytics teams to ensure Databricks and downstream platforms deliver reliable, performant access to large datasets.\nArchitecture & Design\nA defining requirement of this role is the ability to architect data platforms that remain high-performing, highly available, and recoverable at very high data volumes.\nArchitect high-performance database designs capable of sustaining very high transaction and query volumes without degradation.\n Design high-availability (HA) architectures - replication, clustering, failover, and multi-zone/multi-region topologies - to meet demanding uptime targets.\n Design and validate disaster-recovery (DR) strategies, including backup/restore, replication, failover runbooks, and defined RPO/RTO targets, with regular DR testing.\nTranslate business and technical requirements into scalable, resilient, and cost-effective platform designs across PostgreSQL, MongoDB, and Databricks.\nRequired Qualifications\nExtensive hands-on database administration experience, with senior-level depth in PostgreSQL, MongoDB, and Databricks.\nDemonstrated experience scaling data environments for very large data volumes, including sharding, partitioning, replication, and performance tuning at scale.\nDeep expertise in database configuration, optimization, indexing, and query performance tuning.\nProven experience designing and operating high-availability and disaster-recovery solutions for high-volume databases.\nStrong skills in monitoring and observability - instrumenting metrics, dashboards, and alerting to drive proactive operations.\nExperience with capacity planning, maintenance, patching, and upgrade management in production environments.\nSolid command of SQL and a scripting/automation language (e.g., Python, Bash) for operational tooling and automation.\nWorking knowledge of cloud data platforms, storage/compute scaling, and Delta Lake / Spark concepts within Databricks.\nStrong troubleshooting and root-cause analysis skills, with the ability to stay calm and effective during production incidents.\nPreferred Qualifications\nExperience with infrastructure-as-code and automation (e.g., Terraform, Ansible) and CI/CD for database changes.\nFamiliarity with containerization and orchestration (Docker, Kubernetes) for database and data workloads.\nExposure to data governance, security, encryption, and compliance requirements at scale.\nRelevant certifications across PostgreSQL, MongoDB, Databricks, or major cloud providers.\nPrior experience mentoring engineers or leading platform initiatives.\nKey Skills & Attributes\nTechnically savvy - genuinely strong and current across all three platforms, with the instincts to diagnose and optimize complex systems.\nHighly collaborative - works closely with engineering, analytics, and product teams and communicates clearly with both technical and non-technical audiences.\nEager to learn and grow - curious, adaptable, and motivated to expand skills as the data estate and technologies evolve.\nProactive and ownership-minded - anticipates problems, prevents outages, and takes end-to-end responsibility for platform health.\n Detail-oriented and reliable - disciplined about maintenance, documentation, and operational rigor.\nSkan AI is an equal opportunity employer committed to building a diverse, inclusive, and respectful workplace around the world. 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