Things You Need to Have:

• Candidate must have a Bachelors' degree or technical Diploma in Computer Science / Engineering, Data Sciences or a related discipline, or 5 years related work experience
• Candidate must have a minimum of 5 years' experience within the last 7 years working with modern data management principles
• 5+ years' recent experience in ETL, data design, data architecture, data management, and data modeling

Core Technical Skills:

• SQL Server & SSIS: Expert proficiency with SQL Server (on-premises), including stored procedures, and SSIS package-level deployment.
• Data Pipelines: Proven experience designing, creating, and maintaining robust data pipelines and ETL processes.
• Monitoring: Skilled in monitoring and troubleshooting database issues to ensure compliance with policies and regulations
• Python for ETL: Advanced Python skills applied to developing ETL processes following software development best practices (including automated testing and code reviews).
• Big Data Tools: Proficient in leveraging big data technologies, including PySpark and SparkSQL for large-scale data processing.
• Cloud Expertise: Hands-on experience with cloud-based platforms such as Databricks, Azure Data Factory, and Azure Data Lake.
• Lakehouse Architecture: Knowledgeable in implementing lakehouse architectures using Delta format and optimization strategies.
• API Integration: Experience working with external third-party APIs as ETL sources, including Microsoft Graph APIs to integrate and automate tasks across Microsoft services.
• Automation & Deployment: Familiar with CI/CD processes and tools-including Databricks asset bundles (DABs) for managing workflows-and proficient with version control systems (e.g., Git) for ETL deployments.
• Understanding of data management principles as outlined by DAMA/DMBoK
• Ability to provide insights on evolving database integration, storage, and utilization needs
• Overseeing integration from legacy/on-premises systems to new solutions
• Clear communication of technical information and the ability to train/support staff
• Knowledge of data privacy and confidentiality regulations (e.g., PIPEDA)