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Ronald James

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Principal Data Engineer

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Overview

As Principal Data Engineer, you lead the evolution of a next‑gen data platform, shaping architecture, platform design, and long‑term data strategy. You act as a technical authority, owning roadmaps and ensuring security, scalability, and alignment with business goals while staying hands‑on to prototype complex solutions. You collaborate across engineers, architects, and stakeholders to remove blockers and drive delivery. This role offers high impact in shaping platform engineering practices within a forward‑looking tech organization.

Responsibilities
  • Design and implement secure, high-performance Databricks environments including cluster setup, governance, and tuning
  • Define and own the technical roadmap for the organisation’s data platform
  • Ensure systems meet standards for performance, security, maintainability, and reliability
  • Drive progress toward Service Level Objectives (SLOs)
  • Collaborate with technical leads and architects to shape data solutions that meet product and business needs
  • Support cross-functional teams in removing technical blockers and enabling delivery
  • Maintain clear, high-quality technical documentation for data and BI systems
  • Act as a visible, collaborative technical voice within the business
  • Contribute to estimation and technical planning
  • Align all solutions with the wider technical strategy
  • Work with Solution Architects and Analysts to design scalable, forward-thinking solutions
  • Apply architectural principles such as domain modelling and modular design
  • Collaborate with team leads to guide delivery and implementation
  • Provide hands-on support through code reviews, prototyping, and pair programming
  • Support incident response efforts and assist with resolving critical technical issues
  • Rapidly gain deep knowledge of internal BI tools and systems
  • Create and maintain technical documentation, including integration guides and data contracts
  • Support onboarding and knowledge transfer across teams
  • Stay current with modern best practices in data engineering and architecture
Key requirements
  • Proven experience designing large-scale data platforms and Databricks infrastructure
  • Strong understanding of Databricks internals, including cost and performance optimisation
  • Advanced Python skills and software development best practices (e.g. testing, abstraction, modularity)
  • Familiarity with modern data architecture (e.g. Lakehouse, domain-driven design, data contracts)
  • Experience owning and driving platform-level technical roadmaps
  • Active engagement with new technologies and the wider data engineering community
  • Excellent collaboration and communication skills
  • Strong organisational and time management skills
  • A proactive, self-starting mindset with a focus on delivery and ownership
  • collaboration
  • communication
  • proactiveness
  • Databricks
  • Python
  • data architecture

Skills

See also

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