Lead end-to-end software delivery for regulatory reporting systems within Payments Technology. Develop, review, debug, and optimize secure production code, data pipelines, and reporting workloads using Python, PySpark, Spark, and Databricks. Establish AI-assisted engineering practices, validation standards, automation, and SDLC governance. Partner with stakeholders on data quality, lineage, reconciliation, and audit controls while providing technical direction and serving as a subject matter expert.
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer at JPMorganChase within the Corporate and Investment Bank (CIB) Payments Technology – Regulatory Reporting, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Owns end-to-end technical delivery for Regulatory Reporting initiatives; remains hands-on as a senior individual contributor
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale
- Builds and optimizes data pipelines and reporting workloads using Databricks Lakehouse (Delta Lake, Spark SQL, PySpark)
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Partners with stakeholders to deliver controls for regulatory submissions (data quality, lineage, reconciliation, audit evidence)
- Serves as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
Required qualifications, capabilities, and skills
- Bachelor's Degree in Computer Science/ Information systems/ Engineering or related disciplines
- Minimum of 8 years of hands-on software development experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s) (Python required)
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls
- Ability to tackle design and functionality problems independently with little to no oversight
- Practical cloud native experience (AWS preferred)
- Hands-on experience with PySpark/Apache Spark and Databricks (Delta Lake/Lakehouse)
- Good exposure to Payments and Regulatory Reporting domains
Preferred qualifications, capabilities, and skills
- Experience with agentic AI patterns for engineering automation and operational workflows (within approved environments)
- Experience with data quality/reconciliation frameworks for regulatory reporting
- Experience with CI/CD and automated testing for data pipelines
- Exposure to AWS data services (e.g., S3, Glue, Lambda, Step Functions, EMR)
- Exposure to observability tooling (logs/metrics/traces) for production support
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorganChase Singapore, Singapore, SGP Office
One@Changi City, Changi Business Park Central 1, Singapore, Singapore, 486036
Similar Jobs
Big Data • Cloud • Software • Database
Leads a pre-sales solutions architecture team across the ASEAN region. Responsibilities include recruiting and developing talent, partnering with enterprise sales teams, qualifying technical opportunities, advising customers, supporting bookings growth, and strengthening pre-sales practices. The role also collaborates with Professional Services and Marketing on customer success, seminars, trade shows, and other events. The position is based in Singapore under a hybrid model and requires travel of up to 30%.
Top Skills:
AWSGCPAzureMongoDBMongodb Atlas
Big Data • Cloud • Software • Database
Leads pre-sales technical strategy for complex MongoDB opportunities, including discovery, architecture design, demonstrations, proof of value, ROI/TCO analysis, executive engagement, and customer adoption. Partners with sales, customer success, services, and ecosystem teams to modernize legacy systems, design scalable cloud and hybrid architectures, and support AI initiatives. Creates reusable technical assets, generates demand through workshops and events, mentors peers, and advises technical and business stakeholders.
Top Skills:
Ai/MlAtlas Data LakeAtlas SearchAtlas Stream ProcessingAtlas Vector SearchAWSCC#C++Cloud ComputingDistributed SystemsEvent-Driven ArchitecturesGCPJavaAzureMongoDBMongodb AtlasMongodb ChartsNode.jsPythonRelational MigratorRetrieval-Augmented GenerationSQLVector Search
Fintech • Mobile • Payments • Software • Financial Services
Coordinate APAC safeguarding controls across payments, e-money, and investment businesses. Responsibilities include supporting compliant product launches, maintaining risk and controls matrices, coordinating first-line assurance and annual audits, preparing MAS regulatory reports, managing incidents and control failures, resolving reconciliation discrepancies, and documenting the end-to-end control environment. The role partners with controllers, product managers, engineering, and global teams while supporting regulatory change initiatives.
What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
