We are looking for an experienced Data Engineer (Lead) with strong expertise in Databricks to design, develop, and maintain scalable data pipelines and data processing solutions. Key Responsibilities • Design, develop, and maintain scalable data pipelines using Databricks. • Develop data processing solutions using PySpark and Python. • Work with Apache Spark for large-scale data processing. • Build and optimize ETL/ELT pipelines. • Work with Delta Lake for data storage and processing. • Develop and manage workflows using Databricks Workflows. • Perform data transformation, cleansing, and validation. • Optimize Spark jobs and improve pipeline performance. • Collaborate with data engineers, analysts, and other technical teams. • Troubleshoot data pipeline issues and ensure data quality. Required Skills • 3–5 years of experience in Data Engineering. • Strong hands-on experience with Databricks. • Good knowledge of PySpark and Python. • Strong understanding of Apache Spark. • Experience with Delta Lake and data lake architecture. • Good knowledge of SQL. • Experience in building ETL/ELT data pipelines. • Understanding of cloud platforms such as Azure, AWS, or GCP. • Experience with Git and CI/CD is an added advantage. Good to Have • Experience with Azure Databricks. • Knowledge of Azure Data Factory, ADLS, or similar cloud data services. • Experience with DBT, Snowflake, or other modern data platforms. • Databricks certification is a plus. What We Offer • Opportunity to work on real-world Data Engineering and AI projects. • Exposure to modern data technologies and cloud platforms. • Collaborative and learning-focused work environment. • Opportunity to work with a growing technology team.