JPMorgan Chase
Lead Software Engineer- Data Engineer/Pyspark/Databricks
Houston, TX · Full-time · Posted Oct 9, 2026
About the job
Leads engineering for a secure, scalable KYC and risk assessment data platform, developing production software and guiding teams in reusable data engineering and AI-assisted practices.
What you'll do
- Develop and review secure, high-quality production code; mentor engineers and create reusable frameworks and patterns.
- Drive adoption of advanced engineering practices and advise cross-functional teams on technical matters.
- Lead responsible use of enterprise-authorized AI-assisted engineering tools, with validation standards for security, correctness, and quality.
What they ask for
- Practical experience delivering system design, application development, testing, and operational stability at enterprise scale.
- Expertise in one or more programming languages, particularly Python and/or Java.
- Experience with large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools, and orchestration frameworks.
- Advanced knowledge of relational and NoSQL databases, vector stores, data lake architectures, data governance, and cloud-native platforms (AWS, Azure, or GCP).
Nice to have
- Experience with Databricks or Snowflake and hands-on Spark/PySpark or other big data technologies.
- Expertise in Apache Iceberg or LLM orchestration and model-serving infrastructure, including AWS Bedrock or Azure OpenAI.
Tools
Python, Java, Kafka, Redis, MemCached, Dynatrace, Splunk, Grafana
AI focus
Leads responsible adoption of AI-assisted engineering tools for coding, reviews, testing, troubleshooting, and automation; validates outputs for correctness, performance, and security and coaches engineers on safe, compliant use. Preferred work includes LLM orchestration and model serving.
Model-written summary · the original posting is authoritative