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: Segment Customer.io HubSpot Braze Klaviyo 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 Initial Interview (communication, PM, light technical discussion) Foundational Technical Interview Take-Home Assignment (3–7 days) 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
