Simple Machines

Data architecture, engineering, science, and apps

Director Technology - Data Platform Engineering

Engineering LeadershipConfirmed live in the last 24 hours

Full-timeSydney NSW, AustraliaNo salary listedHybrid

About the Job

Requirements

At least 10 years of experience across hands-on 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.
Experience architecting and delivering modern cloud-native data platforms at enterprise scale.
Strong experience developing solutions centered on 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 operationalized data products across large organizations.
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 Google Cloud Platform, Amazon Web Services, Microsoft Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, and machine-learning/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.
Comfort operating in a fast-moving, high-performance consultancy environment.

Responsibilities

Help define and evolve the company's data-platform propositions, technical direction, and strategic positioning.
Advise enterprise clients on modern data-platform strategy, architecture, operating models, and AI readiness.
Support organizations as they evolve from traditional centralized data platforms toward AI-native, real-time, and data-product-oriented operating models.
Work closely with Engagement Managers and senior leadership across major strategic initiatives.
Lead architecture and technical direction for complex enterprise data-platform and transformation programs.
Act as a senior technical counterpart across strategic client engagements and partner relationships.
Support pre-sales, proposal development, technical solution shaping, and executive stakeholder engagement.
Build trusted relationships with strategic technology partners and stay current with emerging platform capabilities and market direction.
Support recruitment, mentor teams, uplift capability, and contribute to practice development across the broader engineering organization.
Lead major client initiatives across data engineering, platform modernization, AI enablement, and operational data systems.
Contribute to thought leadership, market positioning, and growth initiatives across ANZ.

Director Technology - Data Platform Engineering

Simple Machines · Sydney, Australia (Hybrid) · — · Posted 2026-05-21

Workplace: hybrid

Department: Leadership

Description

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

This is a strategic and hands-on Engineering 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 Engineering leader who understands where enterprise data platforms are heading over the next five years, not where they were five years ago.

Requirements

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 hands-on 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.

About Simple Machines

Simple Machines is a global, independent technology consultancy operating across Sydney, New Zealand, London, Poland and San Francisco. We design and build modern data platforms, intelligent systems, and bespoke software at the intersection of Data Engineering, Software Engineering and AI.

We help enterprises, scale-ups, and government turn complex, high-value data into products, platforms, and decisions that drive real impact.

We don't do generic. We build things that matter - We engineer data to life™.

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About the Company

Simple Machines

Data architecture, engineering, science, and apps

Simple Machines is an Australian consulting firm that combines data architecture, data engineering, data science and software development to build large-scale, distributed data platforms and machine learning applications. They design end-to-end data systems that process streaming and batch data at massive scale and help clients operationalize analytics and AI in real-world apps. Unlike firms that offer only consulting or only training, they pair hands-on implementation with formal partnerships—Confluent for Kafka, Databricks for Spark, and Lightbend for Scala—across advisory, implementation, and training. Their goal is to help enterprises, governments, and global tech companies unlock the value of their data through scalable, reliable data pipelines and AI workloads.

Company size: 11-50
Company stage: Not listed
Total funding: Not listed
Headquarters: Sydney NSW, Australia
Founded: 2008

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