Data Engineer

Are you a hands-on Data Engineer passionate about building reliable data pipelines, optimizing data processing, and developing scalable data solutions? Join our team and help strengthen enterprise data platforms using Microsoft Azure, Azure Databricks, SQL, and Python (PySpark). We're looking for a skilled professional with experience delivering end-to-end data projects who can transform raw data into reliable, high-quality datasets that support business intelligence, analytics, and data-driven decision-making. Key Responsibilities Design, develop, and maintain data storage solutions, database objects, data structures, and data ingestion pipelines. Build and optimize data transformation, cleansing, and preparation processes using SQL and Python (PySpark). Improve and automate data engineering jobs through code enhancements, configuration changes, and new technologies. Perform unit testing and system integration testing to ensure data quality, reliability, and performance. Monitor and maintain enterprise data platform stability, execute updates and patches, and ensure compliance with data governance, security, and SDLC standards. Qualifications Has at least 8 years of experience in data engineering projects, with at least one completed end-to-end data project . Hands-on experience with Microsoft Azure and Azure Databricks ; relevant certifications are an advantage. Strong proficiency in SQL and Python (PySpark) for data processing and transformation. Solid understanding of data warehousing, data marts, and query optimization techniques. Ability to collaborate with cross-functional teams to identify data requirements and improve data solutions. Strong documentation skills and an understanding of data engineering best practices, platform governance, and security standards. Azure Data Engineer, Data Engineer L3, Microsoft Azure, Azure Databricks, Databricks Engineer, Python Developer, PySpark Developer, SQL Developer, Data Pipeline Development, ETL/ELT, Data Ingestion, Data Transformation, Data Cleansing, Data Warehousing, Data Mart, Query Optimization, Cloud Data Engineering, Data Integration, Data Analytics, Power BI, Enterprise Data Platform, Data Governance