Sr Lead Software Engineer - Big Data Pyspark, Java And AWS

JPMorganChase•Wilmington, NC

About The Position

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 Consumer and Community Banking cards Technology Team, 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. Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. As a Lead Data Engineer , you will play a key role on an agile team focused on enhancing, building, and delivering secure, stable, and scalable solutions for data collection, storage, access, and analytics. You will leverage your deep technical expertise and problem-solving skills to drive significant business impact, addressing a wide range of challenges across multiple data pipelines, architectures, and data consumers.

Requirements

Formal training or certification in software engineering concepts and 3+ years applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced in one or more programming language(s) - Java
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.
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
Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
Ability to tackle design and functionality problems independently with little to no oversight
Practical cloud native experience
Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field

Nice To Haves

Knowledge on Snowflake
Experience with building Data lake, built Data platforms, built Data frameworks, Built/Design of Data as a Service AP
In-depth knowledge of the financial services industry and their IT systems

Responsibilities

Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
Develops secure and high-quality production code, and reviews and debugs code written by others
Drives decisions that influence the product design, application functionality, and technical operations and processes
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
Influences peers and project decision-makers to consider the use and application of leading-edge technologies
Adds to the team culture of diversity, opportunity, inclusion, and respect
Design and develop end-to-end data pipelines using Spark SQL, Java, and AWS services
Utilize programming languages such as Java and Python, work with NoSQL databases and SQL, and leverage container orchestration services including Kubernetes, along with a variety of AWS tools and services
Define and implement database backup, recovery, and archiving strategies
Generate advanced data models for one or more teams using firmwide tools, linear algebra, statistics, and geometrical algorithms and approve data analysis tools and processes to ensure consistency and quality