Senior Data Engineer - PySpark

<p>Job Description :</p><p><br/></p><p>We are looking for a Senior Data Engineer with strong expertise in Azure Databricks, PySpark, and distributed computing to develop and optimize scalable ETL pipelines for manufacturing analytics.

The role involves working with high-frequency industrial data to enable real-time and batch data processing.<br/><br/>KRA :<br/><br/>Build scalable real-time and batch processing workflows using Azure Databricks, PySpark, and Apache Spark.<br/><br/>- Perform data pre-processing, including cleaning, transformation, deduplication, normalization, encoding, and scaling to ensure high-quality input for downstream analytics.<br/><br/>- Design and maintain cloud-based data architectures, including data lakes, lakehouses, and warehouses, following Medallion Architecture.<br/><br/>- Deploy and optimize data solutions on Azure (preferred), AWS, or GCP with a focus on performance, security, and scalability.<br/><br/>- Develop and optimize ETL/ELT pipelines for structured and unstructured data from IoT, MES, SCADA, LIMS, and ERP systems.<br/><br/>- Automate data workflows using CI/CD and DevOps best practices, ensuring security and compliance with industry standards<br/><br/>- Monitor, troubleshoot, and enhance data pipelines for high availability and reliability.<br/><br/>- Utilize Docker and Kubernetes for scalable data processing.<br/><br/>- Collaborate with automation team, data scientists and engineers to provide clean, structured data for AI/ML models.</p> (ref:hirist.tech)