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Head of Data - Following Australian hours!

Key Facts

Remote From: 
Full time
Senior (5-10 years)
150 - 150K yearly
English

Other Skills

  • Problem Reporting
  • Leadership
  • Dealing With Ambiguity
  • Team Management
  • Collaborative Communications
  • Mentorship

Roles & Responsibilities

  • 7–10 years of hands-on experience in Data Engineering, Analytics Engineering, MarTech, or related fields with a practical engineering focus
  • Strong hands-on engineering background—not just architecture oversight—with experience building and maintaining data pipelines/ETL, CDPs, and customer segmentation
  • Experience delivering data architectures and working with data platforms, event tracking, attribution analytics, and marketing automation ecosystems
  • Excellent client-facing communication and stakeholder management skills, with experience in consulting/agency/multi-client environments and ability to operate in fast-paced, ambiguous settings

Requirements:

  • Design and implement modern data architectures, pipelines, and customer data systems; own solution architecture across ingestion, warehousing, transformation, and activation; hands-on with engineering implementation, integrations, and troubleshooting
  • Lead client engagements end-to-end, including technical discovery, scoping, solution planning, translating complex technical concepts into business language, and supporting pre-sales
  • Lead and mentor a distributed technical team across multiple regions; establish scalable delivery processes, QA standards, and AI-first ways of working; build reusable frameworks and playbooks
  • Shape the company’s technical direction across data engineering, AI-enabled delivery, customer data platforms, and marketing operations; contribute to architecture and delivery standards

Job description

Head of Data & Engineering (Remote – APAC Hours)

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

About the Company

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.

The Role

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.

What You’ll Be Doing

Technical Leadership & Delivery

  • 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

Client Engagement

  • 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

Team & Process Leadership

  • 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

What We’re Looking For

Required Experience

  • ~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

Technical Skills

  • SQL

  • Python

  • Node.js

  • Cloud data platforms / modern data stack

  • dbt or similar transformation frameworks

  • CDPs and engagement platforms such as:

  • Automation tooling (nice to have):

    • n8n

    • Make

    • AI agents / workflow orchestration

Nice to Have

  • 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

Working Style

  • Highly autonomous and proactive

  • Comfortable balancing leadership with execution

  • Fast-moving, iterative mindset

  • Strong ownership mentality

  • Collaborative communicator across technical and business teams

Hiring Process

  1. Initial Interview (communication, PM, light technical discussion)

  2. Foundational Technical Interview

  3. Take-Home Assignment (3–7 days)

  4. Technical Presentation & Final Interview

Additional Notes

  • 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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