Lead Data Platform Engineer

Lead Data Platform Engineer

About the Organisation:

We are a fast-growing, international consumer business with operations across multiple markets. Technology and data play an increasingly important role in how we operate, make decisions and develop new digital capabilities.

Our technology landscape includes a number of core systems and applications, supported by a modern, cloud-based data ecosystem. As the organisation continues to grow, we are investing further in our data capabilities and the foundations that enable teams to make effective use of data.

The Data & AI Team:

Our Data & AI team provides the foundation that enables the organisation to use data effectively - from ingestion and transformation through to analytics, reporting, machine learning and AI-powered solutions.

Our current data platform includes:

• Snowflake — Data Warehouse
• Estuary & Fivetran — Data Ingestion
• dbt Cloud — Data Modelling & Transformation
• Terraform — Infrastructure as Code
• AWS — Cloud Infrastructure
• GitHub Actions — CI/CD

We work closely with Engineering, Corporate IT and stakeholders across a range of business functions.

Our ambition is to provide a reliable, secure, scalable and easy-to-use data foundation that enables teams to build data products, analytics and AI solutions without needing to manage the complexity of the underlying infrastructure.

We already have strong Data Engineering capabilities, particularly across data modelling, transformation and pipeline development. We are now looking to strengthen our Data Platform capability and mature how the underlying platform is architected, operated and scaled.

To support this journey, we are looking for a Lead Data Platform Engineer.

The Role

As Lead Data Platform Engineer, you will take technical ownership of the organisation's foundational data platform.

This is a hands-on technical leadership role combining engineering, architecture and strategic thinking. You will be responsible for evolving the platform's architecture, infrastructure, reliability, security, governance and engineering practices.

While Data Engineers primarily focus on ingestion, transformation and business-facing data products, your focus will be on ensuring the platform itself is:

• Reliable and resilient
• Scalable
• Secure
• Automated
• Observable
• Cost-efficient
• Easy for engineering teams to use

You will act as the steward of the data platform, balancing immediate business requirements with long-term platform strategy and ensuring technology investments support both current needs and future growth.

You will work closely with Data Engineers, Engineering, IT, external partners and business stakeholders to build and operate a modern, scalable data ecosystem.

Key Responsibilities:

Platform Architecture & Engineering

• Own and evolve the architecture of a Snowflake-based data platform.
• Develop and maintain platform infrastructure using Terraform and Infrastructure as Code principles.
• Establish standards and best practices for platform configuration, development and deployment.
• Build and improve CI/CD, DataOps and platform automation capabilities.
• Establish monitoring, logging, alerting and observability across platform services and critical data workloads.
• Improve platform reliability, incident detection, troubleshooting and recovery processes.
• Optimise Snowflake and associated workloads for performance, scalability and cost efficiency.
• Implement scalable approaches to platform security, IAM, RBAC, service accounts and secrets management.
• Build reusable platform capabilities and automation that accelerate Data Engineering delivery.
• Evaluate emerging technologies and platform capabilities where they provide meaningful engineering or business value.

Technical Leadership & Platform Strategy

• Act as the technical authority for the data platform and help define its strategic direction and architectural roadmap.
• Translate business requirements into sustainable platform capabilities and technical solutions.
• Make pragmatic architectural decisions that balance speed, reliability, maintainability, cost and future scalability.
• Drive platform modernisation initiatives and continuously improve operational maturity.
• Establish engineering guardrails that enable teams to move quickly while maintaining platform stability and security.

Stakeholder Management & Communication

• Partner with Data & AI leadership, Engineering, IT and business stakeholders to understand platform requirements and priorities.
• Build strong relationships across technical and non-technical teams to create alignment around platform objectives and investments.
• Communicate platform strategy, roadmaps, risks, dependencies and trade-offs clearly and in a business-oriented manner.
• Act as a key point of contact for platform-related decisions and technical guidance.
• Provide transparency around platform performance, reliability, security posture and cost optimisation.
• Influence decision-making by presenting technical recommendations in a way that clearly articulates business value and impact.

Governance & Decision Making

• Establish governance frameworks, architectural standards and engineering policies across the data platform.
• Evaluate new technologies, vendors and platform solutions based on business value, technical fit, security, scalability and total cost of ownership.
• Drive platform standardisation to reduce complexity, operational risk and technical debt.
• Ensure alignment with organisational security, privacy and risk management requirements.
• Define and monitor platform KPIs relating to reliability, performance, cost efficiency and operational maturity.
• Lead technical reviews and architectural decision-making processes.

Team Leadership & Mentoring

• Mentor Data Engineers and technical contributors on platform best practices, operational excellence and modern engineering principles.
• Promote a culture of ownership, accountability, automation and continuous improvement.
• Lead technical discussions and help engineering teams make effective platform-related decisions.

What You Bring:

Technical Expertise

• 8+ years' experience in Data Platform Engineering, Data Engineering or a related field.
• Experience taking technical ownership of production data platforms and business-critical infrastructure.
• Strong understanding of modern cloud data platform architectures, including ingestion, storage, transformation and orchestration.
• Strong hands-on experience with Snowflake.
• Experience with data ingestion technologies such as Fivetran and/or Estuary.
• Practical experience with Terraform or comparable Infrastructure as Code technologies.
• Experience implementing CI/CD pipelines and modern DevOps practices, ideally using tools such as GitHub Actions.
• Strong experience with cloud technologies, particularly AWS.
• Practical experience establishing monitoring, observability and alerting for production systems.
• Experience optimising platform performance, reliability and cost at scale.
• Strong programming skills in Python and SQL, with experience working with Git.
• Strong experience with dbt and modern data transformation practices.

Leadership & Stakeholder Management

• Demonstrated ability to influence technical direction across multiple teams without direct authority.
• Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
• Proven experience building trust and credibility with senior stakeholders.
• Ability to balance competing priorities and make risk-based decisions in dynamic environments.
• Strong facilitation, stakeholder management and consensus-building skills.
• Ability to challenge assumptions and drive constructive discussions around architectural and strategic decisions.

Strategic & Commercial Mindset

• Ability to evaluate technology and vendor solutions through both technical and commercial lenses.
• Strong understanding of platform economics, total cost of ownership and operational efficiency.
• Experience developing platform roadmaps and contributing to long-term technology strategy.
• Ability to connect technical decisions to measurable business outcomes.

Desirable Experience

• Experience working with retail, transactional or high-volume time-series data.
• Experience with observability technologies such as Grafana.
• Experience with metadata management, data lineage, data quality and data observability tooling.
• Experience leading platform transformation or modernisation initiatives.

What Success Looks Like:

Success in this role is not only measured by platform reliability and technical excellence.

You will also be successful when you are able to influence decisions, align stakeholders, improve engineering maturity and ensure the data platform consistently delivers measurable business value.

The successful candidate will be both a hands-on technical leader and a trusted advisor, helping shape the future direction of the organisation's data platform.

Interested?

If you're an experienced Data Platform Engineer who enjoys combining hands-on engineering with architecture, technical leadership and strategic thinking, we'd love to hear from you.