Senior Solution Engineer (Python)

We are looking for a hands-on senior solution engineer who can design build and operate robust cloud-native data and AI solutions. The ideal candidate combines strong software engineering fundamentals with deep practical experience in AWS and Snowflake.

You will have the following responsibilities:

• Design build and operate production-grade software and data solutions end-to-end from problem definition and architecture through implementation deployment monitoring and continuous improvement.
• Design and implement reliable scalable secure and well-governed data pipelines and data products using AWS and Snowflake across structured semi-structured and unstructured data sources.
• Model curate and optimise Snowflake datasets schemas and data structures in line with enterprise platform standards ensuring performance quality consistency and usability for downstream consumers.
• Apply strong software engineering practices including clean code modular design automated testing CI/CD observability secure development and maintainable architecture.
• Partner with business and technical stakeholders to translate requirements into robust data solutions prioritise delivery and identify opportunities to enable advanced analytics and AI use cases.
• Use AI-assisted engineering as a standard part of daily development work to accelerate coding refactoring documentation testing debugging and solution exploration while maintaining strong engineering judgement and quality standards.
• Build cloud-native integrations and automation on AWS making effective use of services such as compute storage networking security orchestration event-driven architectures and managed AI services where appropriate.
• Own deployment release and production operations including troubleshooting root-cause analysis performance tuning incident resolution peer code reviews pair programming and reuse of proven engineering patterns.

You will have the following qualifications:

• Bachelors or Masters degree in Computer Science Software Engineering Data Science Artificial Intelligence / Machine Learning or a related technical discipline.
• 7 years of professional experience in a hands-on software engineering solution engineering or data engineering role with a proven track record of delivering production-grade systems in enterprise environments.
• Demonstrated ability to build and operate data products cloud services or AI-enabled solutions with measurable business outcomes and clear operational ownership.
• Deep hands-on AWS experience is required including practical knowledge of core services for compute storage networking identity and access management security orchestration monitoring and serverless or event-driven architectures. AWS certification is preferred ideally AWS Certified Solutions Architect - Associate AWS Certified Data Engineer - Associate or AWS Certified Machine Learning Engineer - Associate.
• Deep hands-on Snowflake experience is required including data modelling SQL performance tuning pipeline integration access control cost/performance optimisation data sharing and platform governance. SnowPro Core Certification or advanced Snowflake certifications are a plus.
• Strong proficiency in Python and/or Java with solid understanding of software design principles APIs automated testing packaging dependency management and production maintainability.
• Experience with AWS AI services including Amazon Bedrock and familiarity with agent-based AI solution patterns retrieval-augmented generation model evaluation guardrails and responsible AI practices is preferred.
• Demonstrated habit of using AI-assisted engineering tools such as GitHub Copilot Claude Cursor or similar tools as part of everyday development to improve productivity code quality testing documentation and delivery speed.
• Familiarity with harness engineering or similar AI-assisted development concepts including structuring prompts evaluation loops reusable development workflows automated checks and feedback mechanisms to improve reliability repeatability and engineering quality.
• Strong hands-on engineering mindset with a focus on code quality sound design decisions maintainability and effective collaboration in team-based environments.
• Strong familiarity with the software development lifecycle Git-based workflows CI/CD infrastructure-as-code concepts automated testing DevOps practices and production support.
• Ability to translate ambiguous business problems into clear technical scopes iterative delivery plans and measurable success criteria.
• Comfortable working with sensitive and confidential data and partnering with governance risk and security stakeholders to embed controls from the start.
• Strong collaboration and communication skills with the ability to work closely with business stakeholders and cross-functional technology teams.
• Preferred: background in the financial industry with an understanding of financial markets data sensitivity regulatory expectations and enterprise risk controls.

Required Skills:

PythonSnowflakeSQLAWSAIML