Lead Software Engineer - Python​/PySpark​/Databricks​/AWS

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As a Lead Software Engineer - Python/PySpark/Databricks/AWS at JPMorgan

Chase within the Corporate 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. 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.

• 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
• Drives team adoption of enterprise‑authorized AI‑assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI‑assisted code review/refactoring, test strategy acceleration, incident/root‑cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise‑authorized AI‑assisted development and automation capabilities, to improve the value realized by automation

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Demonstrated experience leading effective use of approved AI‑assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Hands‑on practical experience delivering system design, application development, testing, and operational stability
• Experience building and operating Databricks Lakehouse solutions hosted on Amazon Web Services (AWS), including Amazon S3, Identity and Access Management (IAM), Key Management Service (KMS), basic networking concepts (VPC/security groups), and logging/auditing
• Experience using Delta Lake (ACID‑compliant tables, partitioning strategies, schema evolution) and Apache Spark on Databricks, including performance optimization (cluster sizing, skew mitigation, join strategies, caching, and file sizing/compaction)
• Experience delivering batch and streaming data pipelines (Structured Streaming, incremental processing, backfills, late‑arriving data handling) and implementing governance/security controls in Databricks (e.g., Unity Catalog, table/column‑level permissions, credential passthrough where applicable), with operational ownership including monitoring/alerting, incident response, root‑cause analysis (RCA), and service level objective/service level agreement (SLO/SLA) management
• Advanced in one or more programming language(s) including Python, Py Spark
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Architect Databricks Lakehouse solutions, including bronze/silver/gold (or equivalent)…