Lead Data Engineer – Data Architect – GCP

We are seeking a highly experienced and hands-on Lead Data Engineer to join our growing data team. This role is critical to designing, implementing, and scaling our modern data infrastructure to support business intelligence, analytics, and operational needs across
multiple regions. You will drive architectural decisions, own pipeline design, and guide best practices across the data platform.

Responsibilities:

Architecture & Design

• Design and implement scalable, efficient data models to support analytics and operational systems.
• Define and apply best practices for data change tracking, historical data versioning, and schema evolution.
• Architect the most effective data flow and storage strategies for both real-time and batch data based on business requirements.
• Make informed decisions about pipeline design, storage formats, and performance trade-offs to ensure speed, reliability, and cost-efficiency.

Data Engineering
• Build and manage robust pipelines that support both streaming and batch data processing.
• Establish automated workflows for data transformation, validation, and deployment.
• Ensure performance and cost optimisation across data processing layers and storage tiers.
• Maintain end-to-end reliability, from data ingestion through modelling and exposure to consumers.

Governance & Quality
• Define and enforce standards for data quality, access control, privacy, and compliance.
• Monitor and audit pipeline integrity and data health using automated rules and metrics.
• Ensure secure handling of sensitive data and design solutions for regulatory compliance and retention policies.
• Promote transparency and trust through documentation, versioning, and data lineage tracking.

Leadership & Collaboration
• Provide technical leadership across projects and mentor less experienced engineers.
• Partner with analytics, product, and engineering teams to deliver high-impact solutions.

• Lead decision-making on data design patterns, frameworks, and scalable system architecture.
• Set and uphold standards for development, review, deployment, and incident response processes.

Requirements:

• 7+ years of experience in data engineering, including 2+ years in a leadership or architectural role.
• Deep knowledge of distributed data systems, modelling techniques, and large-scale processing patterns.
• Proficiency in SQL and Python, with strong practices around testing, modularisation, and code review.
• Experience designing secure and auditable data workflows in regulated environments.
• Strong understanding of both traditional and modern data platforms, including streaming and event-driven architectures.
• Experience in cloud storage is a must, especially in GCP.
• Hands-on experience with modern data tooling, including orchestration, transformation, and warehouse optimisation using Airflow, BigQuery, Dataflow, and dbt.

Preferred Qualifications
• Exposure to infrastructure automation, workflow orchestration, and BI enablement practices.
• Familiarity with data access layers and semantic modelling for self-service analytics.
• Demonstrated ability to balance velocity, quality, and maintainability in data platform design.

****MUST be able to demonstrate:

1. Architectural depth – a track record of designing and scaling complex systems.
2. Recent, hands‑on delivery – the ability to drop into code, ship features, and mentor by example on day one.
3. Leadership maturity – credibility to influence stakeholders and raise the bar across multiple squads.

This is an opportunity to shape a foundational layer of the organisation’s data capabilities while leading the charge on engineering best practices, architecture, and team culture. If you’re passionate about data and enjoy building modern, efficient, and reliable systems—this
role is for you.