Director - Data Platform Engineering

We are looking for an experienced and hands-on Director - Data Platform Engineering to lead the design, development, and evolution of a large-scale cloud-native data platform built on Google Cloud Platform (GCP). This role requires a strong engineering leader with deep expertise in distributed data systems, real-time streaming architectures, modern lakehouse platforms, and scalable data engineering practices. The ideal candidate should have experience leading high-performing engineering teams while driving platform scalability, reliability, observability, and AI-readiness across globally distributed environments. You will work closely with Product, Architecture, and Business stakeholders to build reusable platform capabilities and enable standardised, data-driven solutions across multiple regions and business domains.

Responsibilities:

• Lead and mentor high-performing engineering teams focused on scalable data platform development.
• Drive end-to-end ownership of platform capabilities, including architecture, development, deployment, reliability, and operations.
• Partner with Product Managers and Architects to build scalable and reusable data platform solutions.
• Design and implement modern cloud-native data architectures aligned with enterprise standards.
• Build highly scalable batch and real-time data processing systems on GCP.
• Drive engineering excellence across data engineering, DevOps, CI/CD, observability, and platform reliability.
• Ensure systems are optimised for scalability, fault tolerance, performance, and cost efficiency.
• Collaborate with global and cross-functional teams to enable reusable data products and platform services.
• Lead initiatives around data governance, schema management, data quality, lineage, and platform standardisation.
• Evaluate emerging technologies and lead proofs-of-concept for next-generation data platform capabilities.
• Foster a strong engineering culture with a focus on ownership, accountability, innovation, and continuous improvement.
• Enable AI-ready platform capabilities supporting MLOps, feature engineering, and ML workflows.

Requirements:

• 14+ years of overall experience with 8+ years in Data Engineering, Data Platforms, or Distributed Data Systems.
• Strong experience leading large engineering teams in product-based or enterprise-scale environments.
• Experience working in globally distributed and federated engineering organisations.

GCP and Data Platform Expertise:

• Strong hands-on expertise in Google Cloud Platform (GCP), including: BigQuery, Data warehousing, Query optimization, Partitioning & clustering, Cost optimization, Dataflow (Apache Beam), Large-scale batch processing, Streaming pipelines, Fault-tolerant distributed processing, Pub/Sub, Real-time ingestion, Event-driven architecture, Streaming systems, Cloud Composer (Airflow), Workflow orchestration, DAG management, Pipeline scheduling, Google Cloud Storage (GCS), Data lake/lakehouse architectures, Staging and storage optimization.

Technical Expertise:

• Strong understanding of modern Data Lakehouse architectures on GCP.
• Expertise in building end-to-end scalable data pipelines from ingestion to transformation and serving layers.
• Deep understanding of real-time streaming systems, schema evolution, event modelling, and distributed processing.
• Strong programming expertise in Python and Spark (Scala preferred).
• Hands-on experience implementing CI/CD pipelines for data platforms.
• Strong understanding of analytical data modelling and optimisation techniques in BigQuery.
• Experience with data contracts, schema governance, metadata management, and reusable data products.
• Exposure to Data Mesh and event-driven platform architectures.
• Familiarity with MLOps and AI-enabled data platforms, including: Feature engineering pipelines, Model training workflows, Inference pipelines, Vertex AI integration (preferred).

Reliability and Platform Engineering:

• Strong focus on platform observability, monitoring, alerting, lineage, and data quality frameworks.
• Experience managing cost-performance optimisation across GCP services.
• Understanding of platform reliability engineering and operational excellence practices.
• Experience building scalable, resilient, and highly available distributed systems.

Leadership and Stakeholder Management:

• Proven ability to build and scale high-performing engineering teams.
• Strong stakeholder management and cross-functional collaboration skills.
• Ability to influence teams across multiple geographies and business units.
• Excellent communication and leadership capabilities.
• Strong product mindset with focus on platform adoption and reusable engineering capabilities.