Are you a well-rounded Senior Azure Data Engineer with a passion for architecting scalable, efficient, and secure data solutions? Join our esteemed team at INGRITY, where your skills will play a crucial role in serving our clients effectively. Location: Sydney. Employment Type: Full-Time. Eligibility: Open to candidates with full working rights in Australia. About INGRITY: INGRITY is a Microsoft Data and AI Solution Partner dedicated to delivering transformative data and AI-driven solutions. We collaborate with some of the best ASX-listed companies and medium-sized businesses, working closely with Microsoft to create measurable value for our customers. Our success is built on innovation, customer advocacy, and a strategic partnership with Microsoft. About the job: We’re looking for a skilled professional who combines deep hands-on data engineering expertise with strong solution architecture and data modeling capabilities along with expert-level SQL and strong Python skills to design and deliver impactful data platforms on Azure. Key Responsibilities: Collaborate with stakeholders to gather requirements and define project goals. Design and implement end-to-end data solutions on Azure, including data ingestion, transformation, modeling, storage, and analytics. Develop robust ETL/ELT pipelines using SQL and Python , ensuring scalability, efficiency, and quality. Architect data solutions leveraging Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Azure SQL Database , and Data Lake Storage . Build and maintain efficient data models (star/snowflake schema) to support reporting and analytics. Create architecture diagrams, technical documentation, and implementation plans. Set up and manage CI/CD pipelines and deployment automation using Azure DevOps or similar tools. Apply cloud best practices using the Well-Architected Framework (WAF) and Cloud Adoption Framework (CAF) . Implement data security, governance, and monitoring using Azure-native tools. Provide technical leadership and support across the entire project lifecycle. Required Skills & Experience: 5 years of experience in Azure Data Engineering or solution architecture. Hands-on experience with key Azure services including ADF (Azure Data Factory), Azure Databricks, Synapse, Azure SQL Database, and Data Lake Storage . SQL Expert - Advanced experience in writing, optimizing, and troubleshooting complex SQL queries, stored procedures, and database performance. Strong Python Skills - Proficient in Python for data manipulation, transformation, and scripting within data engineering pipelines. Strong background in data modeling for analytics and reporting, including dimensional modeling techniques. Experience designing ETL/ELT workflows , ingesting data from structured/unstructured sources (CSV, JSON, Parquet, APIs). Familiarity with CI/CD processes, Git, pull requests, and release management. Knowledge of Azure security best practices , including IAM, encryption, and role-based access. Proficiency in monitoring tools like Azure Monitor, Log Analytics , and Databricks utilities. Strong problem-solving skills, attention to detail, and ability to work independently. Experience with PySpark or Spark in Databricks. Exposure to real-time data processing tools (e.g., Event Hub, Stream Analytics). Knowledge of data cataloging and governance tools (e.g., Azure Purview). Familiarity with DevOps practices in data environments. About INGRITY: We are a fast-growing, progressive Sydney-based data & analytics company. We service many large corporates and SMBs in the financial services sector, to derive value from data. At Ingrity, we are committed to building a diverse and inclusive workforce to deliver value to customers. As a value-driven organisation, we nurture and support our people by having a laser-sharp focus on skill and talent development, collaboration, and flexibility.