Jobs → Data & Analytics → Data Engineer

About the Role We are looking for a Data Engineer to join our team and work on designing, developing, and supporting data ingestion and transformation pipelines using Databricks and AWS services. Key Responsibilities • Design, develop and maintain batch and/or streaming data pipelines using Databricks and AWS services • Build data ingestion and transformation processes using SQL, Python/PySpark and Delta Lake • Process and organize data across Bronze, Silver and Gold layers using the Medallion Architecture • Integrate data from APIs, databases, files, object storage and other enterprise data sources • Implement data-quality checks, validation, reconciliation, logging, error handling and recovery mechanisms • Troubleshoot and optimize Spark jobs, data processing performance, storage and cloud resource utilization • Support CI/CD, system integration testing (SIT), user acceptance testing (UAT), production deployment and operational handover • Prepare technical documentation and collaborate with platform, application, BI and data-governance teams Requirements • Minimum 3 years of relevant experience in Data Engineering or enterprise data-platform delivery • Hands-on experience in Databricks Data Engineering is essential • Good working knowledge of PySpark, Apache Spark and SQL • Experience with Delta Lake and layered data architecture, such as Bronze, Silver and Gold • Experience developing and supporting production data pipelines, including logging, error handling and recovery • Familiarity with AWS services such as Amazon S3, IAM, AWS Glue, Lambda or Kinesis • Understanding of data modeling, data quality and performance optimization • Strong analytical, troubleshooting and problem-solving skills • Able to work collaboratively, take ownership of assigned tasks and maintain proper technical documentation