KF - Data Engineer - 0062

AI overview

Design and develop data pipelines using Azure technologies while collaborating with cross-functional teams to deliver high-quality data solutions and optimize performance.

We are seeking an experienced and skilled Data Engineer to join our team. As a Data Engineer, your primary responsibility will be to design, develop, and maintain data pipelines and solutions using modern technologies. You should have expertise in SQL with a focus on data warehousing, as well as experience with Azure Databricks, PySpark, Azure Data Factory, and Azure Data Lake. Strong knowledge of data engineering fundamentals and working with Parquet/Delta tables in Azure Data Lake. Proficiency in Python programming and the ability to create data pipelines is necessary.

Job Responsibilities

    • Designing and developing data pipelines to extract, transform, and load data from various sources into the data warehouse leveraging Python & notebooks.
    • Writing complex SQL queries for data extraction and manipulation from the data warehouse.
    • Building and maintaining ETL processes using Azure Databricks with PySpark.
    • Implementing data integration workflows using Azure Data Factory.
    • Collaborating with cross functional teams including developers, data analysts, and business stakeholders to understand requirements and deliver high quality solutions.
    • Optimizing performance of the data pipelines and ensuring scalability and reliability of the systems.
    • Monitoring Data quality and troubleshooting issues in collaboration with the operations team.
    • Maintaining documentation of the design and implementation of the data pipelines.
    • Ability to collaborate on best practices in code creation while maintaining communication with the team for new business logic transformations. 

Requirements

    • Expertise in SQL, ideally with experience in working with data warehousing concepts.
    • Strong firsthand experience with Azure Databricks and Spark.
    • Proficiency in designing and implementing data integration workflow using Azure Data Factory.
    • Demonstrates proficiency in Python programming and the ability to develop scalable data engineering pipelines in Python.
    • Solid understanding of data engineering fundamentals including data modeling, data transformation, change data capture and performance optimization techniques.
    • Experience working with Azure Data Lake for storing large data sets, maintaining Parquet/Delta tables, and performing efficient querying.
    • Experience with version control systems and familiarity with CI/CD practices.
    • Strong interpersonal skills, ability to clearly communicate, and voice concerns in a group setting. 
    • Initiative-taking, self-reliant approach with a willingness to learn business logic and work with critical faults. Candidates should be able to independently understand business requirements without relying on subject matter experts for ongoing explanations. 
    • Ability to collaborate effectively in planning and refinement sessions.

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