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Data Engineer
3 months ago
Key Accountabilities:
- Estimate, design and develop scalable, optimized data pipelines to enable our business through Business Intelligence and Advanced Analytics solutions.
- Develop and update standards and best practices, use DevOps Continuous Integration and Delivery (CI/CD) process.
- Provide hands-on data integration support as part of daily operations; this includes monitoring, configuration, troubleshooting, user administration, and optimizing data objects for consumers.
- Follow ITIL processes to transition activities from project to production.
- Conduct root cause analysis and resolve incidents reported by monitoring systems and end-users.
- Configure and administer tools such as HVR, Magnotix, PowerBi, Tableau, and Informatica for reporting and data integration.
- Establish and maintain best practices and data engineering templates and standards for each toolset and function, ie. ML/AI vs BI Analytics.
Skills & Qualifications:
- Post-secondary degree in Computer Science/Software Engineering or a related field of study or equivalent experience in data integration or data engineering.
- 5+ years experience developing cost-optimized, scalable and configurable ETL/ELT data pipeline or data integration.
- 5+ years of experience with Python, SQL, and PySpark; DevOps/CI/CD pipelines, performant data stores and operational REST APIs.
- Experience in Cloud environments and tools including MS Azure, AWS, Databricks, Synapse Analytics, Data Lakes, Azure Data Factory, HVR, Magnotix, KQL, Scala, PowerBi, Tableau, and Informatica.
