Software Engineer III - Python / Databricks
Software Engineer III in JPMorganChase's Investment Banking Data Products team (posted under Aumni) in Glasgow: designing, building, and maintaining scalable ETL data pipelines, data models, and analytics solutions using Python, Databricks, SQL, and cloud data services like AWS Glue, with a focus on data security, testing, and AI-assisted development.
- Compensation
- Not disclosed
- Location
- Glasgow, United Kingdom
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- Formal training or certification on software engineering concepts and proficient applied experience
- Good working knowledge of cloud-based data services (especially Glue jobs and Federated Data Lake), unified analytics platforms, and Python
- Experience across the data lifecycle, including ingestion, transformation, storage, and access patterns
- Advanced proficiency in SQL, including joins and aggregations, with a working understanding of NoSQL databases
- Significant experience with statistical data analysis and choosing appropriate tools and data patterns for analysis
- Experience utilizing cloud services for developing, deploying, and managing applications at scale
- Working knowledge of SDLC tools for configuration management, CI/CD pipelines, unit testing, regression testing, and performance testing
- Hands-on experience using AI-assisted software development tools (coding, testing, troubleshooting, documentation) with ability to validate AI-generated outputs
- Understanding of responsible AI use in engineering workflows, including data sensitivity, secure input/output handling, and resiliency/security expectations
Nice to have
- Familiarity with standardized data layer practices such as Medallion architecture
- Exposure to relational database platforms and cloud data warehousing solutions
- Curiosity and foundational understanding of generative AI, large language models, and AI/ML solutions
- Skills in designing efficient data models, including normalization, denormalization, schema design, and relational/star schemas
Full description
Are you ready to shape the future of data engineering at JPMorganChase? Join a dynamic team where your unique skills will help build innovative solutions and contribute to a winning culture. You'll have opportunities for career growth, collaborate with talented professionals, and make a real impact on our business objectives. Your expertise will empower our teams and drive success across the firm.
As a Software Engineer III at JPMorganChase within Investment Banking Data Products, you will design and deliver reliable data collection, storage, access, and analytics solutions that are secure, stable, and scalable. You will develop, test, and maintain essential data pipelines and architectures, supporting various business functions to achieve the firm's goals. Working alongside talented engineers, you will use your skills to drive innovation and help shape our team culture — one built on excellence, collaboration, and continuous improvement.
Job responsibilities
- Develop workflows and extract, load, and transform pipelines using Python and Databricks to support scalable and reliable data solutions
- Support the review of controls to ensure sufficient protection of enterprise data across the data lifecycle
- Implement data security using entitlements frameworks to safeguard sensitive information
- Update logical and physical data models based on evolving business use cases and requirements
- Apply SQL expertise — including complex joins and aggregations — and leverage working knowledge of NoSQL databases to support diverse data access patterns
- Apply reuse-first, AI-assisted practices to strengthen software development lifecycle quality routines for data pipelines (e.g., test generation and control validation), ensuring traceability, auditability, and alignment to resiliency and security expectations
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards
- 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
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and proficient applied experience
- Good working knowledge of cloud-based data services (especially Glue jobs and Federated Data Lake), unified analytics platforms, and Python
- Experience across the data lifecycle, including ingestion, transformation, storage, and access patterns
- Advanced proficiency in SQL, including joins and aggregations, with a working understanding of NoSQL databases