JD: Senior Database Engineer - MySQL

Location: Gurgaon-Onsite

Type: Full-time

Experience: 6-10 years
Reports to: IT Head Posted: 10 August 2026

About the role
We are hiring a Senior Database Engineer who builds - designs schemas, writes and tunes SQL, and automates database housekeeping.
You will be working on financial transaction systems, where correctness is not negotiable: money movement, order and payment records, ledgers, and reconciliation data. We need someone who has handled that class of data before and understands why a schema shortcut there costs more than it save.

Key Skills

- Data purging & archival management. Classify hot, warm and historical data; identify obsolete and duplicate records; define data retention and archival policies; implement validated, low-impact purge jobs with pre/post reconciliation and rollback paths.

Outcome - Reduced database size, improved query performance, lower storage cost, faster backups.

- Automated slow-query detection & safe termination. Build the automation yourself using the slow query log, Performance Schema / sys views and pt-query-digest: detect long-running and blocking queries and safely terminate non-critical runaway sessions under explicit safety rules - thresholds, allow/deny lists and a kill audit trail. Document the design and the runbook.

Outcome - Prevents system hangs, avoids CPU spikes, ensures secure application performance.

- Missing index identification & optimization. Analyse query patterns and execution plans; identify missing, redundant, duplicate and unused indexes; implement a coherent indexing strategy - composite column order, covering indexes, selectivity versus write cost - with measured before/after evidence.

Outcome - Faster query execution, reduced I/O load, improved user response time.

- Constraint & data integrity management. Validate and enforce primary keys, foreign keys, unique and check constraints and referential integrity; detect and remediate existing violations; add guardrails that stop duplicate or inconsistent data at write time.

Outcome - Improved data accuracy, prevention of duplicate or inconsistent records.

- Performance tuning - instance & database level. Tune MySQL and InnoDB: buffer pool sizing and instances, redo log and flush behaviour, thread and connection handling,



sort/join and temp-table buffers, cache sizes, isolation and locking behaviour - validated under real load, not by rule of thumb.

Outcome - Improved throughput, reduced latency, predictable performance under load.

- Query fine-tuning. Rewrite inefficient SQL: eliminate full table scans, fix join order and access paths, restructure correlated subqueries, replace OFFSET-based pagination with keyset pagination, and remove N+1 and fetch-all-then-filter patterns alongside the application teams.

Outcome - Lower CPU and memory usage, faster application workflows.

- Schema design & configuration review, with documentation. Design tables for new features and refactors - structure, datatypes, normalisation versus deliberate denormalization, key design, partitioning, migration path and backward compatibility. Review others' schema changes before they ship. Maintain the ER diagrams, data dictionary and configuration baselines.

Outcome - Long-term scalability, reduced technical debt, easier future enhancements.

- Daily database health monitoring. Instrument and watch CPU, memory, disk I/O, replication status and lag, locks, waits, connection saturation and growth trends; set thresholds that mean something; use trend data for capacity forecasting.

Outcome - Early detection of issues, reduced downtime, proactive incident prevention.

- Transactional correctness & financial data integrity. Design for money-safe behaviour: idempotency keys on payment and order paths, correct isolation levels for balance and ledger updates, deadlock-resistant transaction ordering, append-only ledger patterns, and precise numeric types (DECIMAL, minor units) - never floating point for monetary values.

Outcome - No double-debits, no lost updates, books that reconcile.

- Retention under regulatory constraint.



Build purge and archival policies that respect statutory retention for financial and KYC records - archive-then-purge rather than delete, with audit trails and restorability, so cost reduction never breaches a retention obligation.

Outcome - Smaller live database without compliance exposure.

- Auditability. Ensure financial tables carry the audit trail an auditor or regulator will ask for - change history, who and when, and traceability from transaction to settlement - designed in, not bolted on later.

Outcome - Audits and reconciliations pass without forensic archaeology.
Must-have qualifications

- 7+ years hands-on with MySQL in production, in a design and development capacity - you have designed schemas and built database code.
- Prior experience in the fintech / BFSI domain - banking, payments, broking, lending, wealth, insurance or a similar regulated financial environment.
- Demonstrable experience modelling financial data: transactions, orders, payments, ledgers, balances or settlement and reconciliation flows.
- Sound grasp of transactional correctness for money movement - ACID in practice, isolation levels, idempotency, no-double-debit design, exact numeric handling for currency.
- Solid InnoDB understanding buffer pool, MVCC, locking and deadlocks, replication.
- Proven experience designing schemas from scratch for transactional systems and refactoring live schemas safely.
- Expert SQL and execution-plan analysis (EXPLAIN / EXPLAIN ANALYZE), with the judgement to know when an index is the wrong fix.
- Hands-on experience implementing retention, archival and purge on large tables, including where regulatory retention periods apply.
- SQL plus Python or Shell scripting - enough to build your own jobs, checks and validation harnesses.
- Performance tuning backed by before/after measurement, not guesswork.
- Experience with online schema change tooling and low-downtime migrations.
- Working knowledge of monitoring tooling (Grafana or CloudWatch).

Good to have

- Aurora - parameter groups, read replicas, failover behaviour.
- Partitioning and sharding; multi-hundred-GB to TB tables.
- Backup and restore design with tested RPO and RTO.
- Familiarity with data-protection and audit expectations in financial systems.

What this role is not

- Not "watch dashboards and escalate" - you design the fix and implement it.

📌 Senior Database Engineer (Gurugram)
🏢 Parahit Technologies
📍 Gurugram