Software Engineer Data Analyst Jobs in Houston, TX

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As a Lead Software Engineer at JPMorganChase within the Corporate Technology - Data protection and Recovery product line, 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 breakdown technical problems
• Develops secure and high-quality production code, and reviews and debugs code written by others
• 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.
• 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
• Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms
• Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
• Evaluates and reports on access control processes to determine effectiveness of data asset security with minimal supervision
• Create reports in JIRA, Confluence, and other platforms as needed, to improve product line reporting workflow, JIRA and resource analysis, Sprint results and efficiency, other metrics

• 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
• Strong Python programming skills, including unit and integration testing
• Strong SQL skills and experience with SQL-based transformation tooling.
• Experience designing and operating orchestration pipelines using Airflow or similar tools
• Experience designing and building streaming pipelines using Kafka, Pub/Sub, or similar messaging systems
• Experience and proficiency across the data lifecycle
• Demonstrated experience delivering in an agile, fast-paced engineering environment
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

• Experience in building application using Java Spark.
• Experience with AWS cloud technologies.
• Experience with data governance frameworks.
• Understanding of incremental data processing and versioning.
• Understanding of RESTful APIs and web technologies.