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Data Engineering Architect

1 week ago


Sydney, New South Wales, Australia INGRITY Full time
About Ingrity

We are a progressive data and analytics company delivering actionable insights to drive impact. Our expertise lies in leading and delivering major data transformation programs in large and medium enterprises in Australia.

Our clients range across banking, insurance, retail, law, underwriting, and real estate. We provide superior business expertise and extensive experience in data and technology implementations.

Our Culture

  • We thrive on the fusion of Intelligence & Grit.
  • Prioritising personal growth, open communication, continuous learning, career progression, and accountability.

About the Job

We seek an experienced Azure Solutions Architect with strong expertise in data engineering to join our team. You will collaborate closely with prestigious clients, contribute to their success, and design end-to-end data solutions on the Azure platform.

Your Responsibilities:

  1. Collaborate with clients and stakeholders to gather requirements and define project objectives.
  2. Build trusted advisor relationships across client stakeholders by understanding their needs and technologies.
  3. Design and architect data solutions on Azure using services such as Azure Synapse Analytics, Azure Data Factory, Azure Databricks, and Azure SQL Database.
  4. Develop architecture diagrams, technical documentation, and implementation plans.
  5. Optimize data solutions for performance, scalability, and cost-effectiveness.
  6. Provide technical leadership and guidance to development teams throughout the project lifecycle.
  7. Oversee the entire data delivery process for new projects, including change management, requirements gathering, development, testing, and migration to production.
  8. Implement and deploy Azure-based data solutions across the Microsoft platform, leveraging ADF.
  9. Support data governance activities and advocate for best practices within data warehousing.
  10. Set up and maintain CI/CD pipelines to support the data warehouse, ensuring efficient and automated deployment processes.
  11. Demonstrate proficiency in Well-Architected Framework/Cloud Adoption Framework (WAF/CAF) and extensive technical expertise in managing cloud and hybrid infrastructures at an enterprise scale, covering architecture design, migration strategies, and technology governance.

Your Technical Skills and Experience:

  • With over 5 years of proven expertise as a Solutions Architect in the data domain, including extensive experience in data engineering and a specialized focus on Azure technologies.
  • In-depth expertise in Azure services relevant to data engineering and analytics, such as Azure Databricks, Azure Data Lake Storage, Azure SQL Database, Azure Synapse Analytics, and Azure Data Factory.
  • Proficiency in programming languages such as Python, SQL, and optionally R, Scala, and Java for data manipulation, analysis, modelling, and integration.
  • Understanding of data modelling concepts and experience designing efficient data models for analytics and reporting. Proficiency in developing ETL/ELT workflows using tools like Azure Data Factory and Databricks.
  • Knowledge of data integration patterns and techniques for ingesting data from various sources into the Azure ecosystem. Experience with data ingestion tools, data formats (e.g., CSV, JSON, Parquet), and data connectors.
  • Experience in developing CI/CD pipelines and change management. Understanding of branching strategies, pull requests, and code reviews.
  • Knowledge of Azure security best practices, data encryption, identity and access management (IAM), and data governance.
  • Skills in monitoring Azure services and Databricks clusters for performance, resource utilization, and cost optimization using tools like Azure Monitor, Azure Log Analytics, and Databricks monitoring.
  • Deep understanding of analytics' business-driving capabilities and championing a culture of data-driven decision-making.
  • Attention to detail, ability to identify gaps in information, manipulate complex datasets, and exhibit strong data cleaning skills.
  • Highly motivated with excellent time management skills, capable of working independently.