Lead Analytics Engineer

1 day ago

Sydney, New South Wales, Australia Talent Insights Group Full time $180,000 - $250,000 per year

Join a high-performing Analytics Engineering and Insights team as a Analytics Engineer / GenAI Lead that is responsible for identifying, developing, and embedding AI and automation methodologies. Drive their AI roadmap, builds scalable tool stacks, and leads the end-to-end implementation of AI projects. A core focus is on translating business problems into structured AI solutions that reduce manual work, surface insights, accelerate revenue, and foster trust in our AI products among diverse stakeholders.

The Role:

Champion opportunities to apply AI and automation to improve efficiency and effectiveness across diverse business areas. Translate complex or ambiguous business challenges into clear, actionable solutions using the right AI models, APIs, and automation frameworks. Work closely with legal, marketing, and compliance teams to build understanding and trust in AI solutions.

Develop scalable playbooks and best practices that allow AI and automation initiatives to expand efficiently and create lasting capabilities across the organisation.

A strong
data engineering background
is critical for success in this role. It ensures you can design and implement reliable data pipelines, integrate AI models seamlessly into business systems, and build the technical foundations required for automation at scale. This technical depth enables informed decision-making, faster experimentation, and the ability to translate data into tangible business outcomes.

Required technical experience and background:
Lead / Senior Analytics Engineer ( dbt / Airflow / Snowflake )
includes :

  • Comprehensive understanding of the AI landscape, including LLMs, agents, APIs, vector databases, automation tools, and no-code solutions.
  • Hands-on experience building and deploying AI workflows or micro-products, whether in a startup or larger organizational setting
  • 4+ years' experience in data engineering or analytics engineering roles
  • Hands-on experience with dbt Core, Airflow, and Snowflake
  • Strong SQL skills and understanding of data modelling (Dimensional / ELT)
  • Practical hands-on experience with data science tools including Spark, Python, R, TensorFlow, PyTorch, and SQL

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