Codes solutions and unit test to deliver a requirement/story per the defined acceptance criteria and compliance requirements
Designs, develops, and modifies architecture components, application interfaces, and solution enablers while ensuring principal architecture integrity is maintained
Mentors other software engineers and coach team on Continuous Integration and Continuous Development (CI-CD) practices and automating tool stack
Executes story refinement, definition of requirements, and estimating work necessary to realize a story through the delivery lifecycle
Performs spike/proof of concept as necessary to mitigate risk or implement new ideas
Automates manual release activities
Designs, develops, and maintains automated test suites (integration, regression, performance)
Lead architecture, design, and development of large-scale database and data platform solutions
Own end-to-end delivery across technologies including Oracle, MemSQL(SingleStore), Cockroach DB, DB2, ETL (IBM DataStage), and Autosys
Build and optimize high-performance data pipelines supporting real-time and batch processing
Provide technical leadership across development and support
Ensure solutions meet performance, scalability, security, and regulatory requirements
Collaborate with product owners and stakeholders to define, refine, and deliver business requirements
Drive best practices in CI/CD, release management, and production support
Troubleshoot and resolve complex data and system issues as needed.
Contribute to testing strategies and continuous improvement initiatives.
Requirements
12+ years of hands-on experience in database engineering, large-scale data platforms, or backend systems development
Bachelor’s degree in Computer Science, Engineering, IT, Computer Application or job related field required
Deep expertise in relational database design and performance engineering, including Oracle, MemSQL, or comparable enterprise RDBMS platforms like Cockroach DB, IBM DB2
Advanced proficiency in SQL and PL/SQL development, including complex query optimization, stored procedures, and data modeling
Strong experience building and maintaining ETL pipelines using IBM DataStage (or similar tools), including batch processing and orchestration via Autosys or equivalent schedulers
Solid understanding of data architecture principles, including transactional vs. analytical workloads, data partitioning, indexing strategies, and high-availability design
Hands-on experience with Linux/Unix environments, including automation using Python and/or shell scripting
Proven experience in production observability pattern, leveraging tools such as Splunk, Dynatrace, or similar for monitoring, logging, and performance tuning
Experience implementing and supporting CI/CD pipelines, version control workflows, and automated deployment practices in enterprise environments
Strong ability to analyze and troubleshoot complex system and data issues across distributed environments
Demonstrated experience leading technical initiatives, mentoring engineers, and driving delivery across cross-functional teams.