Cloud Data Engineer (AWS / Databricks)

Key Responsibilities: Design, build, and optimize scalable data pipelines and frameworks on AWS leveraging EMR, EKS, S3, and related services. Develop, deploy, and manage Databricks (DBX) workflows for big data processing, analytics, and machine learning. Implement infrastructure as code (IaC) solutions using Terraform for automated provisioning and environment consistency. Write efficient, reusable, and optimized code in Scala, Python, and Java for data transformation, streaming, and integration. Collaborate with architects, data scientists, and business stakeholders to translate requirements into technical solutions. Ensure performance tuning, scalability, and cost optimization across cloud-based data platforms. Enforce best practices in security, CI/CD, testing, and DevOps integration for cloud-native applications. Required

Skills & Experience: 7–10 years of hands-on experience in data engineering and cloud frameworks. Proven expertise with AWS big data services (EMR, EKS, S3, Lambda, Glue).Strong development skills in Scala, Python, and Java. Deep knowledge of Databricks (DBX) for batch and streaming workloads. Solid experience with Terraform for infrastructure automation. Familiarity with CI/CD, containerization (Docker, Kubernetes), and Agile methodologies. Nice-to-Have

Skills: Exposure to machine learning workflows on Databricks. Knowledge of Airflow or other orchestration tools. Experience with data lakehouse architectures.