Job Summary: We are looking for an experienced Database & Data Engineer who can own the full lifecycle of our cloud data systems—from database optimization to building scalable data pipelines. This hybrid role demands deep expertise in SQL performance tuning , cloud-native ETL/ELT , and modern Azure data engineering using tools like Azure Data Factory, Databricks, and PySpark . Ideal candidates will be comfortable working across Medallion architecture , transforming raw data into high-quality assets ready for analytics and machine learning. Key Responsibilities: 🔹 Database Engineering Implement and optimize indexing, partitioning, and sharding strategies to improve performance and scalability. Tune and refactor complex SQL queries, stored procedures, and triggers using execution plans and profiling tools. Perform database performance benchmarking, query profiling , and resource usage analysis. Address query bottlenecks, deadlocks, and concurrency issues using diagnostic tools and SQL optimization. Design and implement read/write splitting and horizontal/vertical sharding for distributed systems. Automate backup, restore, high availability, and disaster recovery using native Azure features. Maintain schema versioning and enable automated deployment via CI/CD pipelines and Git . 🔹 Data Engineering Build and orchestrate scalable data pipelines using Azure Data Factory (ADF), Databricks , and PySpark . Implement Medallion architecture with Bronze, Silver, and Gold layers in Azure Data Lake. Process and transform data using PySpark, Pandas, and NumPy . Create and manage data integrations from REST APIs , flat files, databases, and third-party systems. Develop and manage incremental loads , SCD Type 1 & 2 , and advanced data transformation workflows . Leverage Azure services like Synapse, Azure SQL DB, Azure Blob Storage , and Azure Data Lake Gen2 . Ensure data quality, consistency, and lineage across environments. 🔹 Collaboration & Governance Work with cross-functional teams including data science, BI, and business analysts. Maintain standards around data governance, privacy, and security compliance . Contribute to internal documentation and team knowledge base using tools like JIRA, Confluence, and SharePoint . Participate in Agile workflows and help define sprint deliverables for data engineering tasks. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. 5+ years of hands-on experience in data engineering and SQL performance optimization in cloud environments. Expertise in Azure Data Factory, Azure Data Lake, Azure SQL, Azure Synapse , and Databricks . Proficient in SQL, Python, PySpark, Pandas, and NumPy . Strong experience in query performance tuning, indexing, and partitioning . Familiar with PostgreSQL (PGSQL) and handling NoSQL databases like Cosmos DB or Elasticsearch . Experience with REST APIs , flat files, and real-time integrations. Working knowledge of version control (Git) and CI/CD practices in Azure DevOps or equivalent. Solid understanding of Medallion architecture , lakehouse concepts, and data reliability best practices. Preferred Qualifications: Microsoft Certified: Azure Data Engineer Associate or equivalent. Familiarity with Docker, Kubernetes , or other containerization tools. Exposure to streaming platforms such as Kafka, Azure Event Hubs, or Azure Stream Analytics. Industry experience in supply chain, logistics, or finance is a plus. Show more Show less