Lead Software Engineer - Java, Spark, Kubernetes, AWS, Databricks

Are you ready to make a lasting impact by building and scaling mission-critical systems? At JPMorganChase, you will lead by example, shaping the future of data platforms and services. You'll join a collaborative team that values innovation, technical excellence, and continuous learning. Your expertise will help us deliver resilient, high-performance solutions that power our business. Discover opportunities for growth and advancement as you drive best practices and mentor talented engineers.

Job Summary:
As a Vice President, Lead Software Engineer in our platform engineering team, you will architect, build, and scale data-intensive platforms and services. You will own the design and delivery of high-throughput, low-latency applications, mentor engineers, and drive best practices across cloud-native, batch, and streaming workloads. You will partner with cross-functional teams to translate requirements into secure, reusable APIs and services, ensuring compliance and operational excellence. Your leadership will help shape our technical direction and foster a culture of innovation.

Job Responsibilities:

• Lead architecture and end-to-end delivery of high-throughput, low-latency applications and data pipelines
• Design and implement resilient, observable, and cost-efficient microservices and data processing frameworks
• Build scalable Spark jobs on Databricks, optimize performance, and enforce coding standards
• Define and evolve platform engineering practices including CI/CD, infrastructure-as-code, and automated testing
• Drive Kubernetes-based runtime standards and enforce SRE/operability guardrails
• Partner with product, data, and platform teams to translate requirements into secure APIs, datasets, and services
• Mentor, coach, and conduct code/design reviews for engineers; set technical direction and uphold engineering excellence
• Champion cloud architecture on AWS, including networking, compute, storage, security, and cost governance
• Instrument systems with robust observability and implement runbooks, playbooks, and on-call readiness
• Ensure compliance with data governance, security standards, and regulatory requirements
• Enforce RBAC, encryption, and auditability across platforms

• Strong track record of delivering production systems in software engineering roles
• Expertise in Java (8+) with deep knowledge of concurrency, memory management, and performance tuning
• Advanced experience with Apache Spark and Databricks, including job optimization and Delta Lake patterns
• Hands-on experience with Kubernetes (EKS or equivalent), deploying microservices, and service-to-service networking
• Proficiency in AWS services including IAM, VPC, EC2/EKS, S3, Lambda, Step Functions, and CloudWatch
• Experience with CI/CD tools, infrastructure-as-code, and containerization
• Solid data engineering fundamentals including partitioning, schema evolution, and data quality frameworks
• Practical knowledge of observability stacks, distributed tracing, and production troubleshooting
• Excellent communication and leadership skills
• Ability to influence architecture and guide teams through complex technical decisions
• Commitment to compliance and security standards

• Experience with Databricks Workflows/Jobs, Unity Catalog, and Delta Live Tables
• Familiarity with API design (REST/gRPC), messaging (Kafka/Kinesis), and streaming topologies
• Security-first mindset with experience in secrets management and compliance controls
• Background in financial services or other highly regulated environments
• Exposure to Python/Scala for Spark and SQL performance tuning