Senior Data Engineer (AI & Snowflake) - Hybrid Sydney

Allura Partners

Sydney

Hybrid

AUD 189.000 - 231.000

Vollzeit

Vor 2 Tagen
Sei unter den ersten Bewerbenden

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Benefits dieser Stelle

Hybrid setup
Early access to Snowflake AI tooling
Room to influence platform evolution

Zusammenfassung

Allura Partners seeks a Senior Data Engineer (AI) in Sydney to extend Snowflake environment and run AI workloads alongside data platforms. This individual contributor role focuses on building data pipelines, models, and AI-ready data assets in collaboration with AI engineers.

You will work with Snowflake, Python, SQL and dbt, applying Data Vault principles and embeddings; contribute to platform evolution and enable business teams with scalable AI-enabled data products.

Qualifikationen

  • Deep hands-on Snowflake, SQL, dbt and Python; Snowpark a bonus.
  • Experience using Cortex or Snowflake AI functions on live work.
  • Experience with LLMs, embeddings or vector search.
  • Strong data modeller with Data Vault knowledge preferred.
  • Understand how data needs to be shaped for ML and features.
  • Able to discuss technical work in plain language.

Aufgaben

  • Develop data pipelines and products in Snowflake, adding AI enrichment as data lands.
  • Run LLM and vector search workloads inside the platform.
  • Create data models for reporting and AI, using Data Vault and dimensional methods.
  • Set up monitoring and alerts for AI and data workloads.
  • Help AI engineers connect platform outputs to applications and guide business teams.

Kenntnisse

Snowflake
SQL
dbt
Python
Snowpark
Snowflake AI
LLMs/Embeddings
Data Vault
Data modeling
Plain language

Tools

Cortex
Snowpark

Jobbeschreibung

Allura Partners seeks a Senior Data Engineer (AI) in Sydney to extend Snowflake environment and run AI workloads alongside data platforms. This individual contributor role focuses on building data pipelines, models, and AI-ready data assets in collaboration with AI engineers.

You will work with Snowflake, Python, SQL and dbt, applying Data Vault principles and embeddings; contribute to platform evolution and enable business teams with scalable AI-enabled data products.

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