Director - Data Platform Engineering

We are looking for a senior data leader to join Simple Machines in Sydney as part of our Global Data Practice leadership team.

This is a strategic and hands-on leadership role focused on helping shape the future direction of our data platform capability across ANZ. The individual will play a key role in defining our propositions, strengthening our technical capability, and helping clients modernise their data ecosystems for an AI-native future.

The role requires someone equally comfortable operating at executive, architectural, commercial, and delivery levels. We are looking for a leader who understands where enterprise data platforms are heading over the next five years, not where they were five years ago.

Key Responsibilities

• Part of the Global Data Practice leadership team
• Helping define and evolve Simple Machines’ data platform propositions, technical direction, and strategic positioning
• Advising enterprise clients on modern data platform strategy, architecture, operating models, and AI readiness
• Supporting organisations as they evolve from traditional centralised data platforms toward AI-native, real-time, and data product-oriented operating models
• Working closely with Engagement Managers and senior leadership across major strategic initiatives
• Leading architecture and technical direction for complex enterprise data platform and transformation programs
• Acting as a senior technical counterpart across strategic client engagements and partner relationships
• Pre-sales, proposal development, technical solution shaping, and executive stakeholder engagement
• Building trusted relationships with strategic technology partners and staying current with emerging platform capabilities and market direction
• Supporting recruitment, mentoring, capability uplift, and practice development across the broader engineering organisation
• Leading major client initiatives across data engineering, platform modernisation, AI enablement, and operational data systems
• Contributing to thought leadership, market positioning, and growth initiatives across ANZ.

Must-Haves

• 10+ years’ experience across data engineering, data platforms, analytics engineering, or data architecture
• Proven consultancy and enterprise client-facing experience
• Strong pre-sales, proposal development, and solution shaping capability
• Demonstrated experience architecting and delivering modern cloud-native data platforms at enterprise scale
• Strong experience developing solutions centred around data products and reusable enterprise data capabilities
• Deep understanding of data mesh principles, federated governance, and scalable domain-oriented data ownership models
• Experience designing platforms and architectures to support AI-native use cases, machine learning systems, agentic workflows, and intelligent software platforms
• Strong understanding of real-time and event-driven architectures, including streaming data systems and low-latency processing patterns
• Experience building platforms that support governed, discoverable, reusable, and operationalised data products across large organisations
• Familiarity with contemporary data stack technologies and modern engineering practices
• Strong understanding of platform architecture, distributed data systems, orchestration, governance, and scalable data product design
• Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling
• Strong commercial acumen and ability to engage credibly with senior technical and business stakeholders
• Experience leading major enterprise initiatives and high-performing engineering teams
• Comfortable operating in a fast-moving, high-performance consultancy environment

Ideal Profile

We are looking for someone who combines strong technical depth with commercial and strategic capability. This is not purely a delivery management role, nor is it purely architectural. The ideal person will have a strong point of view on the future of enterprise data platforms, modern data operating models, and the convergence of data engineering and AI enablement.

You should be comfortable moving between executive conversations, whiteboarding architecture, shaping proposals, mentoring teams, and helping clients navigate complex transformation programs.