Data Engineer responsible for designing and maintaining enterprise data warehouse for various projects. Collaborating with stakeholders to ensure efficient data flow and integration.
Responsibilities
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.
Requirements
Bachelor's degree or equivalent in the field of Computer Science or Engineering
3+ years of Proven experience as a Data Engineer, specifically working with Microsoft Azure technologies.
Proficient in T-SQL, Pyspark, Mapping Dataflow and Python programming language
Hands-on experience with Azure data services, including Azure Data Factory, Azure Data Lake, Azure Function App, Azure Logic App, Azure SQL Database, Azure Synapse Analytics, mapping dataflow, and Event Hub.
Understanding of data warehousing concepts and best practices.
Experience with Data modeling.
Experience in working with structured, semi-structured and unstructured data.
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