Senior Database Administrator

On the Job

Uptime & Reliability: Own availability SLOs for production databases. Lead incident response and RCAs for DB-related outages, and drive fixes to closure.
On-call Support: Participate in the 24x7 database on-call rotation, including off-hours and weekend cover. Act as the escalation point for DB incidents raised by SRE and engineering teams, keep runbooks and alert thresholds current, and cut alert noise so pages are actionable.
Performance & Scaling: Profile production workloads (slow query logs, pg_stat_statements, Performance Schema, DynamoDB/Cassandra metrics) and act on them: indexing, query rewrites, partitioning, connection pooling, read replicas, sharding, capacity changes.
Workload Analysis & Decisions: Separate OLTP and analytical access patterns, push back on schemas or queries that will not scale, and make evidence-backed calls on engine choice, instance class and topology.
DR & Multi-Zone Replication: Design and test backup, PITR, cross-AZ and cross-region replication. Plan and execute periodic DR drills with documented RTO/RPO results.
Audit & Compliance: Own database controls for RBI, NPCI, ISO 27001, PCI DSS and third-party audits: access reviews, encryption at rest and in transit, audit logging, data retention, data localisation evidence. Be the point person for auditor walkthroughs.
Cost Optimisation: Right-size instances, reserved capacity and storage tiers; tune DynamoDB capacity modes; retire unused replicas and snapshots. Report spend against usage.
CDC Operations: Operate and tune CDC pipelines (Debezium, Kafka Connect, AWS DMS): replication slots, binlog/WAL retention, schema changes, lag and replay.
Object Storage & Lifecycle: Manage S3 buckets used for backups, archives and the lakehouse. Analyse access patterns and set lifecycle, tiering and retention policies.
Distributed Query Engines: Operate and tune MPP engines such as Trino, StarBurst, StarRocks, BigQuery: cluster sizing, resource groups, caching, query governance.
Design Standards: Define and enforce standards for schema design, naming, indexing, migrations, access roles and PII handling. Review schema changes before they reach production.
Maintenance & Security Upgrades: Own version upgrades, patching, parameter changes and certificate rotation with zero or planned-minimal downtime.
Launch Readiness: Prepare database infrastructure for new product rollouts: capacity plans, load tests, migration runbooks, rollback paths.
Collaboration: Work with backend, data, SRE, security and non-technical stakeholders (compliance, finance, product) and translate DB risk into decisions they can act on.

Must Haves

5-8 years in database administration or database reliability engineering, with at least 3 years on high-traffic, customer-facing production systems.
Deep production expertise in PostgreSQL or PostgresSQL Based, including replication internals, vacuum/InnoDB tuning, and upgrades on both self-managed and RDS/Aurora.
Production experience with at least two of: DynamoDB, Cassandra, MongoDB, Redis.
Proven record of DR drills, multi-AZ/multi-region replication and restoring from backup under pressure.
Direct involvement in regulatory or third-party audits (RBI, ISO 27001, PCI DSS, SOC 2 or equivalent), including producing evidence and closing findings.
Hands-on database cost optimisation with measurable savings.
Strong SQL, query plan analysis and scripting in Python or Bash for automation.
Experience with infrastructure as code (Terraform or CloudFormation) and monitoring stacks (Prometheus, Grafana, CloudWatch, Datadog or similar).
Solid understanding of database security: IAM and role design, encryption, secrets management, audit logging.
Willingness to be part of a 24x7 on-call rotation, with prior experience handling production DB incidents off-hours.

Good to Haves

Operating Debezium / Kafka Connect CDC in production.
Running Trino,Starburst, StarRocks or BigQuery clusters at scale.
S3 lifecycle and storage tiering design for backups and data lakes.
Databases on Kubernetes (operators such as CloudNativePG, Percona, K8ssandra).
Experience in fintech, payments or banking, especially UPI or card systems.
Familiarity with Apache Iceberg / DeltaLake or Lakehouse table formats.
Analysing slow queries generated by BI tools such as Superset, Metabase or Power BI, tracing slow dashboard rendering back to query patterns, missing indexes or unsuitable data models, and fixing them at the source or through aggregates and caching.
Taking part in CI/CD for database changes: migration tooling (Flyway, Liquibase, Alembic or similar), automated schema linting and review gates that enforce design standards before changes reach production.
Certifications: AWS Database Specialty, PostgreSQL, MongoDB or Cassandra.