oracle
Software Engineer III Aws Aurora PostgreSQL DB
JPMorgan Chase
Mumbai, IND
Full-time
Mid · 3+ years experience
Onsite
Discovered 1 weeks ago
awscassandradynamodbjavajenkinspostgresql
Key Skills for This Role
awscassandradynamodbjavajenkinspostgresql
Full Job Posting
Preferred Qualifications
- Experience with Java, Spring Boot, Python, or related programming and scripting languages.
- Familiarity with CI/CD tooling such as Jenkins, Spinnaker, or comparable enterprise deployment platforms.
- Exposure to automation patterns that improve database operations, self-service, monitoring, and incident resolution.
- Experience supporting credit card, banking, payments, or other high-volume financial services applications.
- Ability to translate operational trends into recommendations that improve resiliency, performance, and customer experience.
- Demonstrated interest in continuous learning, technical mentoring, and building strong engineering practices across teams.
Qualifications
- Formal training or certification in database administration, database engineering, software engineering, or related technical discipline and 3+ years of applied experience.
- Hands-on experience administering, supporting, or engineering databases in a large-scale corporate or production environment.
- Practical experience with one or more cloud database technologies, including Cassandra, CockroachDB, Oracle, Aurora PostgreSQL, or DynamoDB.
- Working knowledge of AWS services, cloud infrastructure concepts, and database deployment patterns in resilient production environments.
- Experience with database performance factors, monitoring tools, tuning practices, backup procedures, and recovery approaches.
- Understanding of fault detection, incident response, root cause analysis, and production issue resolution processes.
- Experience implementing or supporting high availability features, including replication, partitioning, failover, and disaster recovery practices.
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
- Knowledge of the Software Development Life Cycle and agile delivery practices, including change management, operational readiness, and release controls.
- Strong written and verbal communication skills, including the ability to influence technical stakeholders and explain database risks, trade-offs, and recommendations clearly.
Responsibilities
- Administer highly available and scalable cloud database environments across Cassandra, CockroachDB, Oracle, Aurora PostgreSQL, and DynamoDB.
- Design database solutions that support application resiliency, performance, security, and operational stability requirements.
- Implement physical data models, database designs, data access patterns, and table maintenance routines aligned to application needs.
- Maintain high availability capabilities through data partitioning, replication, backup, recovery, and failover practices.
- Resolve database performance, capacity, replication, and data integrity issues through structured troubleshooting and root cause analysis.
- Monitor database health, service levels, alerts, and operational trends to identify risks before they impact production stability.
- Optimize database performance using tuning practices, monitoring insights, automation opportunities, and capacity management techniques.
- Execute database upgrades, migrations, patching, and configuration changes with disciplined change management and risk controls.
- Collaborate with application architects, information architects, database designers, and engineering teams to select and implement fit-for-purpose database platforms.
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
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