Revalsys Technologies - Data Engineer - Azure Databricks/PySpark

Job Description

Team full of data scientists, data engineers and business analysts who work with 1M+ data points every day. Market Size : Massive multi-billion $ global market opportunity. Leadership : Combined experience of 40+ years of experience in the industry. Customers : Word-of-mouth and referral driven marketing to acquire customers like big retail brands in GCC regions like Lulu, GMG, among others (Strong product-market fit). What makes us stand apart : 8 years old bootstrapped and 100+ people company that is still hiring. Key Responsibilities Design, develop, and optimize big data pipelines using Azure Databricks, PySpark, and Delta Lake. Work with Azure Data Lake, Azure Synapse, Azure SQL Database, and Azure Data Factory to implement robust data solutions. Develop and maintain ETL/ELT workflows for efficient data ingestion, transformation, and processing. Implement data governance, security, and compliance best practices in Azure environments. Optimize Databricks clusters, workflows, and cost efficiency in cloud environments. Collaborate with data scientists, analysts, and business stakeholders to ensure high-quality data solutions. Implement CI/CD pipelines for data engineering workflows using Azure DevOps. Ensure data quality, lineage, and observability using tools like Great Expectations, Unity Catalog, and Databricks SQL. Certifications Required Qualifications & Skills Databricks Certified Data Engineer Associate (Preffered) Databricks Certified Data Engineer Professional (Preferred) Technical Skills Azure Cloud Services : Azure Databricks, Azure Data Factory, Azure Data Lake, Azure Synapse, Azure Functions Big Data & ETL : PySpark, SQL, Delta Lake, Kafka (preferred) Programming : Python, SQL, Scala (optional) Orchestration & Automation : Airflow, Azure DevOps, GitHub Actions Data Governance & Security : Unity Catalog, RBAC, PII masking Performance Optimization : Spark tuning, Databricks cluster configuration, z-ordering Preferred Experience 2-4 years of experience in data engineering with a focus on Azure and Databricks. Experience working in high-volume, real-time streaming environments. Strong understanding of data modeling, warehousing, and governance best practices (ref:hirist.tech) Show more Show less