Location: Fully Remote (must overlap with Australian business hours)
Compensation: ~AUD $150K fully inclusive
Employment Type: Full-Time, Direct Hire
Experience Level: 7–10 years preferred
Our client is a fast-growing consultancy focused on building scalable growth systems through data, automation, AI, and marketing technology. They partner with ambitious companies to design and implement modern data infrastructure, customer lifecycle systems, and AI-enabled operational workflows.
This is a highly hands-on leadership role for someone who enjoys solving technical problems directly, working closely with clients, and leading distributed technical teams in fast-moving environments.
We’re looking for a Head of Data & Engineering who combines deep technical execution with strong client-facing communication skills.
This is not a purely strategic or management-only role — you’ll be expected to actively contribute to architecture, implementation, troubleshooting, and delivery. You should be comfortable jumping into code, pipelines, CDPs, and automation workflows yourself when needed.
You’ll lead client engagements end-to-end while helping shape the company’s technical direction across data engineering, AI-enabled delivery, customer data platforms, and marketing operations.
Design and implement modern data architectures, pipelines, and customer data systems
Own solution architecture across ingestion, warehousing, transformation, and activation layers
Work hands-on with engineering implementation, integrations, and troubleshooting
Define standards for event tracking, attribution, CDP architecture, and reporting
Evaluate and implement AI-powered workflows and automation opportunities
Lead technical discovery, scoping, and solution planning with clients
Translate complex technical concepts into clear business language
Serve as a trusted advisor for both technical and non-technical stakeholders
Support technical pre-sales conversations and solution proposals
Lead and mentor a distributed technical team across multiple regions
Establish scalable delivery processes and QA standards
Drive AI-first ways of working across the engineering organization
Build reusable frameworks, documentation, and operational playbooks
~7–10 years in Data Engineering, Analytics Engineering, MarTech, or related fields
Strong hands-on engineering background — not just architecture oversight
Experience building and maintaining:
Data pipelines / ETL workflows
CDPs and customer segmentation systems
Marketing automation ecosystems
Event tracking implementations
Attribution and analytics layers
Strong communication and stakeholder management skills
Experience working directly with clients in consulting, agency, or multi-client environments
Comfortable operating in ambiguity and fast-paced environments
SQL
Python
Node.js
Cloud data platforms / modern data stack
dbt or similar transformation frameworks
CDPs and engagement platforms such as:
Segment
HubSpot
Braze
Klaviyo
Automation tooling (nice to have):
n8n
Make
AI agents / workflow orchestration
Background in RevOps, MarOps, Growth, or Marketing Technology
Experience in startups, scale-ups, or consulting environments
Strong interest in AI-enabled operational workflows and automation
Highly autonomous and proactive
Comfortable balancing leadership with execution
Fast-moving, iterative mindset
Strong ownership mentality
Collaborative communicator across technical and business teams
Initial Interview (communication, PM, light technical discussion)
Foundational Technical Interview
Take-Home Assignment (3–7 days)
Technical Presentation & Final Interview
Fully remote role
Must be able to work Australian client hours
APAC candidates strongly preferred due to timezone alignment
Hiring ASAP with onboarding targeted before the end of the month

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