Databricks ML Ops Engineer

Purpose of the role

To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. 

Accountabilities

• Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance.
• Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives.
• Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing.
• Stay informed of industry technology trends and innovations and actively contribute to the organization's technology communities to foster a culture of technical excellence and growth.
• Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions.
• Implementation of effective unit testing practices to ensure proper code design, readability, and reliability.

Assistant Vice President Expectations

• To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
• Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, solve problems creatively and effectively.
• Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Join us as a Databricks ML Ops Engineer at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness technology to revolutionise our digital offerings, ensuring unparalleled customer experiences.

To be successful as a Databricks ML Ops Engineer, you should have:

• Extensive Python programming experience (PySpark, Pandas, data manipulation libraries)
• Previous experience with Databricks platform
• Proficiency in CI/CD processes with tools like GitLab
• Building/ Testing/ Deploying ML models using ML-Ops framework

Some other highly valued skills may include:

• Strong knowledge of cloud ecosystem (AWS, Azure)
• Data visualisation tools such as PowerBI or Tableau
• Good knowledge and experience in data engineering with ETL pipelines Real-time data processing
• Experience in data modelling (star/snowflake schemas, dimensional modelling)

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.

This role will be based in our Prague office.