Azure Data Engineer

As an Azure Data Engineer with 4+ years of experience, your role will involve building and managing large-scale data pipelines using Azure Data Factory (ADF), Databricks (PySpark), and Advanced SQL. You will be responsible for designing, developing, and deploying ETL/ELT pipelines, implementing data ingestion and transformation workflows, and optimizing SQL queries for production workloads. Key Responsibilities: - Design, develop, and deploy robust ETL/ELT pipelines using Azure ADF and Azure Synapse. - Implement data ingestion, transformation, and integration workflows using PySpark on Databricks. - Work with schema-on-read methodologies for large-scale data processing. - Collaborate with cross-functional teams to ensure data quality and reliability. - Optimize SQL queries and pipeline performance for production workloads. Qualifications Required: - Strong proficiency in Advanced SQL, including complex queries, stored procedures, and performance tuning. - Hands-on experience with Azure Data Factory (ADF) for pipeline creation, data flows, and orchestration. - Expertise in Azure Databricks (PySpark) for data transformation, optimization, and integration. - Familiarity with Azure Data Lake Storage (ADLS Gen2) for schema-on-read and big data processing. Additional Company Details: This is a contractual position located remotely with working hours from 11:00 AM to 8:00 PM, with flexibility required as per project needs. Good to have skills include experience with Azure Synapse, Power BI/Tableau reporting exposure, Power BI DAX development knowledge, Python scripting, and familiarity with Terraform or other infrastructure-as-code tools. As an Azure Data Engineer with 4+ years of experience, your role will involve building and managing large-scale data pipelines using Azure Data Factory (ADF), Databricks (PySpark), and Advanced SQL. You will be responsible for designing, developing, and deploying ETL/ELT pipelines, implementing data ingestion and transformation workflows, and optimizing SQL queries for production workloads. Key Responsibilities: - Design, develop, and deploy robust ETL/ELT pipelines using Azure ADF and Azure Synapse. - Implement data ingestion, transformation, and integration workflows using PySpark on Databricks. - Work with schema-on-read methodologies for large-scale data processing. - Collaborate with cross-functional teams to ensure data quality and reliability. - Optimize SQL queries and pipeline performance for production workloads. Qualifications Required: - Strong proficiency in Advanced SQL, including complex queries, stored procedures, and performance tuning. - Hands-on experience with Azure Data Factory (ADF) for pipeline creation, data flows, and orchestration. - Expertise in Azure Databricks (PySpark) for data transformation, optimization, and integration. - Familiarity with Azure Data Lake Storage (ADLS Gen2) for schema-on-read and big data processing. Additional Company Details: This is a contractual position located remotely with working hours from 11:00 AM to 8:00 PM, with flexibility required as per project needs. Good to have skills include experience with Azure Synapse, Power BI/Tableau reporting exposure, Power BI DAX development knowledge, Python scripting, and familiarity with Terraform or other infrastructure-as-code tools.