below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$142,400–$213,500.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
Lead Software Engineer - Big Data
As a Lead Software Engineer - Big Data within the Corporate Sector - Infrastructure Platforms - Data and Specialty Services team, you will join an agile team to build and deliver trusted, scalable technology products. You will design, automate, and operate production-grade ETL and data transformation pipelines while mentoring junior engineers. Your daily work involves gathering requirements to build Spark-based batch and real-time workflows, managing data lake tables in Iceberg and Delta formats, and contributing to platform SDK infrastructure. You will utilize a technical stack including Scala, Python, Java, HBase, Cassandra, Spring Boot, and Docker. Key responsibilities include optimizing costs, implementing CI/CD, and using Grafana and Prometheus for monitoring. You will solve complex data problems by ensuring operational stability and enabling predictive models to run at scale.
Design, build, and operate scalable ETL and data transformation pipelines for production environments.
Develop and optimize Spark-based batch and real-time workflows using Scala, Python, or Java.
Manage large-scale data lake tables using Iceberg and Delta formats.
Implement and maintain CI/CD pipelines and monitoring systems using Grafana and Prometheus.
Create and deploy RESTful APIs using Spring Boot and Docker containers.
Gather technical requirements from stakeholders to design and document software solutions.
Mentor junior engineers and lead communities of practice for new technologies.
Drive the adoption of AI-assisted engineering practices for code review and testing.
What we're looking for
Formal training or certification in software engineering concepts and 5+ years of applied experience.
Advanced proficiency in Python, Java, Scala, Apache Spark, Databricks, Grafana, Prometheus, Elasticsearch, Cloudwatch, Spring Boot API, and containers.
Experience implementing low-latency, scalable data operations and real-time lookups using Apache HBase and Apache Cassandra.
Ability to build and implement scalable ETL pipelines for structured and semi-structured data within Hadoop-based architectures.
Proficiency in managing large-scale data lake tables in Iceberg and Delta formats, including ACID-compliant operations and schema evolution.
Demonstrated experience leading the use of approved AI-assisted software development tools and understanding responsible AI use in engineering workflows.
Advanced understanding of agile methodologies, CI/CD, application resiliency, security, and documenting workflows in Confluence.
In-depth knowledge of the financial services industry and their IT systems (preferred); practical cloud-native experience (preferred).
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Test-Driven Development
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Cloud Computing