Revalsys Technologies - Data Engineer - Databricks/PySpark

<p><p><b>Job description : </b><br/><br/>We are a team of data professionals who work with large datasets every day.

With over 40 years of combined experience, we have a unique approach to data engineering.<br/><br/><b>Key Responsibilities : </b><br/><br/>- Design and develop big data pipelines using Azure Databricks, PySpark, and Delta Lake.<br/><br/>- Work with Azure Data Lake, Azure Synapse, Azure SQL Database, and Azure Data Factory to implement robust data solutions.<br/><br/>- Develop and maintain ETL/ELT workflows for efficient data ingestion, transformation, and processing.<br/><br/>- Implement data governance, security, and compliance best practices in Azure environments.<br/><br/>- Optimize Databricks clusters, workflows, and cost efficiency in cloud environments.<br/><br/>- Collaborate with data scientists, analysts, and business stakeholders to ensure high-quality data solutions.<br/><br/>- Implement CI/CD pipelines for data engineering workflows using Azure DevOps.<br/><br/><b>Required Qualifications & Skills : </b><br/><br/>- Databricks Certified Data Engineer Associate (Preferred)<br/><br/>- Databricks Certified Data Engineer Professional<br/><br/>- Azure Cloud Services : Azure Databricks, Azure Data Factory, Azure Data Lake, Azure Synapse, Azure Functions<br/><br/>- Big Data & ETL : PySpark, SQL, Delta Lake, Kafka (Preferred)<br/><br/>- Programming : Python, SQL, Scala (Optional)<br/><br/>- Orchestration & Automation : Airflow, Azure DevOps, GitHub Actions<br/><br/>- Data Governance & Security : Unity Catalog, RBAC, PII masking<br/><br/>- Performance Optimization : Spark tuning, Databricks cluster configuration<br/><br/>- Experience : years of experience in data engineering with a focus on Azure and Databricks.<br/><br/>- Strong understanding of data modeling, warehousing, and governance best practices</p><br/></p> (ref:hirist.tech)