We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking, 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Develops secure high-quality production code, and reviews and debugs code written by others
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
- Designs and delivers trusted data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way. Defines database back-up, recovery, and archiving strategy
- Generates advanced data models for one or more teams using firmwide tooling, linear algebra, statistics, and geometrical algorithms
- Approves data analysis tools and processes
- Creates functional and technical documentation supporting best practices
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture.
- Design & develop data pipelines end to end using Spark SQL, Java and AWS Services. Utilize programming languages like Java, Python, NoSQL databases, SQL, Container Orchestration services including Kubernetes, and a variety of AWS tools and services.
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Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years of applied experience.
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s)
- Proficiency in automation and continuous delivery methods
- Proficient in all aspects of the Software Development Life Cycle
- Hands-on practical experience in system design, application development, testing and operational stability.
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying language. Hands-on practical experience in developing spark-based Frameworks for end-to-end ETL, ELT & reporting solutions using key components like Spark SQL & Spark Streaming.
- Proficient in coding in one or more Coding languages - Java, Python. Experience with AWS cloud technologies, including S3 . Experience with Relational and No SQL databases,
- Cloud implementation experience with AWS including: AWS Data Services: Proficiency in Lake formation, Glue ETL (or) EMR, S3, Glue Catalog, Athena, Kinesis (or) MSK, Airflow (or) Lambda + Step Functions + Event Bridge. Data De/Serialization: Expertise in at least 2 of the formats: Parquet, Iceberg, AVRO, JSON-LD. AWS Data Security: Good Understanding of security concepts such as: Lake formation, IAM, Service roles, Encryption, KMS, Secrets Manager
- Solid understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security
Preferred qualifications, capabilities, and skills
- Snowflake knowledge or experience preferred
- In-depth knowledge of the financial services industry and their IT systems
- Worked with building Data lake, built Data platforms, built Data frameworks, Built/Design of Data as a Service AP