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SSM Data Tech Lead

Infomedia · Sydney

New
Mid 🇬🇧 English
Databricks Delta Lake Medallion architecture Unity catalog Data governance Data modelling Python PySpark Apache Spark Kafka SQL Materialized views Common Table Expressions AWS S3 CI/CD Git MLflow GenAI Prompt Engineering Fine Tuning Agents

Job description

About the role

We are looking for a Data Tech Lead to join an existing team responsible for building, maintaining and enhancing internal production applications that accelerate product delivery to customers. The role involves implementing new business rules, supporting legacy systems and driving continuous improvement across the data platform.

Key responsibilities

  • Design and deliver technical solutions that meet business and customer objectives.
  • Provide clear feedback on technological constraints to project and technical teams.
  • Develop and support new and existing production processing systems within agreed timelines.
  • Lead continuous improvement and optimisation of data pipelines and processes.
  • Collaborate with project managers on work breakdowns and effort estimates.
  • Create and maintain documentation to enable ongoing support and knowledge transfer.
  • Ensure code quality, data quality checks, error reporting and remediation.

Required profile

  • Minimum 2 years of end‑to‑end Databricks experience on production projects.
  • Hands‑on experience with Databricks Genie, AI/BI dashboards, pipelines, warehouses and job orchestration.
  • Strong background in Delta Lake, Lakehouse and Medallion architectures, including Unity catalog governance.
  • Proficiency in data modelling, ELT/CDC, streaming and cost‑optimisation on Databricks.
  • Solid understanding of AI/ML concepts and general cloud computing (AWS, S3).
  • Experience with CI/CD, Git, Agile SDLCs and automated testing.
  • Excellent communication, analytical and problem‑solving abilities.

Required skills

  • Databricks platform administration and pipeline development
  • Delta Lake, Lakehouse, Medallion architecture
  • Unity catalog and data governance
  • Python, PySpark, Apache Spark, Kafka
  • Advanced SQL (materialized views, CTEs)
  • AWS services, S3
  • CI/CD, Git
  • MLflow, GenAI, LLMs, Prompt Engineering, RAG, Fine‑tuning, Agents

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Published 3 hours ago

Expires 1 month from now

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Infomedia

Sydney