Chief Data Architect

4 days ago

Brisbane, Queensland, Australia beBeeData Full time $120,000 - $170,000
Job Title: Data Engineering Specialist

We are seeking a highly skilled professional to join our data analytics and intelligence team.

  • Maintain strong working relationships with business and technical stakeholders.
  • Develop performant end-to-end data engineering solutions in a collaborative environment.
  • Propose practical solutions to ensure delivery quality.
Key Responsibilities:
  • Lead the design and development of robust data pipelines, data lakes, and data warehouse solutions.
  • Work closely with analysts, architects, and business stakeholders to deliver trusted, high-performance data platforms.
  • Design and implement scalable ETL/ELT workflows with built-in validation and error handling.
  • Build and maintain data pipelines using Snowflake, Informatica IICS, Python, and other modern data integration tools.
  • Integrate central data stores, data warehouses, and data lakes with analytics platforms like Power BI.
  • Apply Agile and DevOps methodologies, including Git, APIs, containers, microservices, and orchestration.
  • Monitor data freshness, completeness, and schema changes using modern observability tools.
  • Implement data governance frameworks (e.g. DAMA-DMBOK) and ensure compliance with privacy regulations.
Requirements:
  • 5+ years of experience in data engineering, data integration, or similar roles.
  • Proven experience with validated implementation of data warehouse, data lakes, or similar data centralisation models with Snowflake, Informatica IDMC, SQL, Python, and MS Power BI.
  • Data Architecture: Experience with design and implementation of data architecture and modelling approaches like Inmon, Kimball, Data Vault.
  • Python programming: Ability to write clean, efficient Python code for data manipulation and analysis.
  • End-to-end data project delivery: Demonstrated success in delivering comprehensive data solutions involving: Data governance, Architecture and modelling, ETL/ELT processes, Data lakes and warehousing, Master Data Management (MDM), and BI.
  • Engineering delivery practices: Experience with Agile and DevOps methodologies, including Azure DevOps version control, APIs, Containers, Microservices, and Data pipeline orchestration, Wiki, Confluence, or similar.
  • Data observability: Monitor data freshness, completeness, and schema changes using modern tools.
  • Data governance: Apply frameworks like DAMA-DMBOK and ensure compliance with privacy regulations.
  • Security and access control: Implement encryption, masking, and role-based permissions for sensitive data.
  • Privacy-aware engineering: Design systems that support anonymisation, pseudonymisation, and data minimisation.

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