Cloud Data Pipeline Developer

As a Data Engineering professional working with Fabric, your role will involve the following key responsibilities: - Data Engineering / Fabric/DevOps/GitHub integration/RBAC/ Medallion Architecture / Fabric OneLake/ ADLS Gen2 Storage - Utilizing Power Automate & Azure functions for efficient data processing - Demonstrating strong SQL skills for querying, transforming, and optimizing large datasets - Proficiency in programming languages such as Python (mandatory) or Scala / Java - Building and maintaining ETL/ELT data pipelines effectively - Applying solid understanding of data warehousing concepts like star schema, snowflake schema, and dimensional modeling - Working with relational and NoSQL databases for data storage and retrieval - Leveraging cloud data platforms like AWS / Azure / GCP for efficient data processing - Experience with Big Data processing frameworks with preference for Apache Spark - Familiarity with workflow orchestration tools like Apache Airflow or equivalent - Applying knowledge of data modeling, data transformation, and data validation techniques - Experience with version control systems like Git for code management - Understanding of data security, governance, and access control for maintaining data integrity Qualifications required for this role include: - Strong experience in Azure ADF, DataBricks, Azure Synapse Analytics, Pyspark, Python, SQL - Total experience of 7-10 years in Data Engineering - Proficient in monitoring, troubleshooting, and optimizing data pipelines in production environments As a Data Engineering professional working with Fabric, your role will involve the following key responsibilities: - Data Engineering / Fabric/DevOps/GitHub integration/RBAC/ Medallion Architecture / Fabric OneLake/ ADLS Gen2 Storage - Utilizing Power Automate & Azure functions for efficient data processing - Demonstrating strong SQL skills for querying, transforming, and optimizing large datasets - Proficiency in programming languages such as Python (mandatory) or Scala / Java - Building and maintaining ETL/ELT data pipelines effectively - Applying solid understanding of data warehousing concepts like star schema, snowflake schema, and dimensional modeling - Working with relational and NoSQL databases for data storage and retrieval - Leveraging cloud data platforms like AWS / Azure / GCP for efficient data processing - Experience with Big Data processing frameworks with preference for Apache Spark - Familiarity with workflow orchestration tools like Apache Airflow or equivalent - Applying knowledge of data modeling, data transformation, and data validation techniques - Experience with version control systems like Git for code management - Understanding of data security, governance, and access control for maintaining data integrity Qualifications required for this role include: - Strong experience in Azure ADF, DataBricks, Azure Synapse Analytics, Pyspark, Python, SQL - Total experience of 7-10 years in Data Engineering - Proficient in monitoring, troubleshooting, and optimizing data pipelines in production environments