- Optionales Büro in Toronto
Description
Purpose of Job:
The Data Engineer will have the responsibility for the design and maintenance of enterprise data warehouse for various projects, as well as providing on-going support for activities impacting all enterprise databases. The ideal candidate will have hands-on experience with Azure Data Factory, Azure Data Lake, Azure Synapse, Azure Function App, Logic App, REST APIs, mapping dataflow, and Event Hub. As a key member of our team, you will collaborate with various stakeholders to ensure efficient data flow, storage, and integration, while employing best practices in data engineering.
Main Activities:
· Design, develop, and maintain scalable Synapse pipelines for data ingestion, processing, and transformation in Azure data platform.
· Develop and optimize T-SQL and Python-based data processing scripts and integrate them with Synapse pipelines for ETL tasks and data transformations.
· Design and develop mapping dataflow solutions for complex data transformations.
· Develop and maintain data storage solutions, ensuring efficient data retrieval and storage on Azure Data Lake and databases.
· Implement and maintain API integrations, including REST APIs, for seamless data flow between systems.
· Design and test the end-to-end process for data ingestion, data transformation, data cleansing, data delivery, data quality and data timeliness.
· Implement and ensure data security and privacy measures, complying with industry standards and regulations.
· Monitor and optimize the performance of Azure data services, Azure Synapse pipelines, Function Apps, and Logic Apps.
· Improve the scalability, efficiency, and cost-effectiveness of data pipelines.
· Participate in Joint Application Development sessions with business units to gather and understand their data and reporting requirements.
· Create and maintain technical documentations for tools, development, and procedures.
· Provide inputs and assist in enablement of Cloud based data solutions.
· Develop and recommend innovative approaches to solve business and technical problems.
· Work and collaborate with the larger team to exchange knowledge, solutions, and practices to build a more consistent, robust approach to development.
· Continuously improve performance and proactively identify and resolve bottlenecks that will reduce time to build and deliver our products.
· Troubleshoot and resolve data-related issues in a timely manner for production and other environments (DEV,UAT,QA)
· Perform business as usual tasks (BAU) that assigned
