Data Engineer SQL Python Cloud

As a Data Engineer at Dynamisch, your role involves designing, building, and maintaining robust data pipelines from multiple sources to data lake/warehouse. You will be responsible for developing transformations using SQL and Python (Spark/Databricks if applicable) with reusable, modular code. Additionally, you will work with Airflow/ADF or equivalent tools to set up retries, alerting, and monitoring for the data pipelines. Key Responsibilities: - Design, build, and maintain data pipelines from multiple sources to data lake/warehouse - Develop transformations using SQL and Python with reusable, modular code - Implement Airflow/ADF or equivalent tools for retries, alerting, and monitoring - Ensure data quality and reliability through validation checks, reconciliation, audit fields, and documentation - Perform data modeling for analytics and enable downstream BI/reporting/ML consumption - Optimize performance and cost through partitioning, incremental loads, query tuning, and efficient storage formats Qualifications Required: - 4-6 years of experience as a Data Engineer - Strong understanding of Power BI or Tableau, Azure Synapse, and similar tools If you are passionate about working in a dynamic Information Technology Solutions and Service Company like Dynamisch, focused on providing end-to-end outsourced product engineering services including software product development, mobile application development, software migration, re-engineering, cloud enablement, and QA & testing services, then this role is perfect for you. As a Data Engineer at Dynamisch, your role involves designing, building, and maintaining robust data pipelines from multiple sources to data lake/warehouse. You will be responsible for developing transformations using SQL and Python (Spark/Databricks if applicable) with reusable, modular code. Additionally, you will work with Airflow/ADF or equivalent tools to set up retries, alerting, and monitoring for the data pipelines. Key Responsibilities: - Design, build, and maintain data pipelines from multiple sources to data lake/warehouse - Develop transformations using SQL and Python with reusable, modular code - Implement Airflow/ADF or equivalent tools for retries, alerting, and monitoring - Ensure data quality and reliability through validation checks, reconciliation, audit fields, and documentation - Perform data modeling for analytics and enable downstream BI/reporting/ML consumption - Optimize performance and cost through partitioning, incremental loads, query tuning, and efficient storage formats Qualifications Required: - 4-6 years of experience as a Data Engineer - Strong understanding of Power BI or Tableau, Azure Synapse, and similar tools If you are passionate about working in a dynamic Information Technology Solutions and Service Company like Dynamisch, focused on providing end-to-end outsourced product engineering services including software product development, mobile application development, software migration, re-engineering, cloud enablement, and QA & testing services, then this role is perfect for you.