Data Engineer III - Python, Databricks

Salary: £62,000 - 102,000 per year

Requirements:

• Formal training or certification in software engineering concepts and 3 years of applied experience.
• Good working knowledge of AWS, Databricks, and Python.
• Experience across the data lifecycle.
• Demonstrated experience using enterprise-authorized AI capabilities in the work environment to support data engineering workflows, with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted outputs before use, escalating when uncertain and following data handling requirements.
• Advanced SQL skills, including joins and aggregations.
• Working understanding of NoSQL databases.
• Significant experience with statistical data analysis and the ability to determine appropriate tools and data patterns for analysis.
• Experience using AWS Cloud Services to develop, deploy, and manage applications at scale.
• Good understanding of software development lifecycle tools used for configuration management, CI/CD pipelines, unit testing, regression testing, and performance testing.
• Familiarity with standardized data layer practices, such as Medallion architecture.
• Exposure to Aurora Postgres and MongoDB.
• Skills in designing efficient data models, including normalization, denormalization, and schema design, with understanding of relational and star schemas.

Responsibilities:

• Develop workflows and ELT pipelines using Python and Databricks.
• Use enterprise-authorized AI capabilities within the work environment to accelerate data pipeline and design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
• Support review of controls to ensure sufficient protection of enterprise data.
• Implement data security using entitlements frameworks.
• Update logical or physical data models based on new use cases.
• Use SQL frequently and work with NoSQL databases.
• Apply reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines, including test generation and control validation, while ensuring traceability, auditability, resiliency, and security alignment.

Technologies:

• AI
• AWS
• CI/CD
• Cloud
• Databricks
• Support
• MongoDB
• NoSQL
• Python
• SQL
• Security

More:

We are a global leader in financial services, providing strategic advice and products to corporations, governments, wealthy individuals, and institutional investors. Our Commercial & Investment Bank operates across banking, markets, securities services, and payments, serving clients in more than 100 countries. We offer a dynamic agile environment with opportunities for career growth, collaboration with talented professionals, and the chance to make a real impact on our business objectives. We value excellence, continuous improvement, diversity, and inclusion, and we build trusted long-term partnerships to help clients achieve their goals. We are an equal opportunity employer and provide reasonable accommodations for religious practices, beliefs, and mental health or physical disability needs.

last updated 34 week of 2026