Lead Data Engineer

7 days ago


New Delhi, India Zyoin Group Full time

Lead Data Engineer Experience:10+ Years Location:Bangalore / Hyderabad / Noida Mandatory Skills:Databricks, AWS, PySpark, AirflowRole Overview We are seeking a Lead Data Engineer to design, build, and maintain scalable data platforms and pipelines. This role requires strong hands-on expertise in cloud-based data engineering, distributed data processing, and workflow orchestration, along with the ability to guide teams and deliver high-quality data solutions in a fast-paced environment.Core Responsibilities Design, develop, and manage scalable and reliable data pipelines usingPySparkandDatabricks . Build and maintain data orchestration workflows usingApache Airflow . Architect, implement, and optimize cloud-based data solutions onAWS . Work extensively with AWS services includingS3, Glue, Redshift, EMR, Lambda, and IAM . Ensure high performance, reliability, and scalability of large-scale data processing systems. Perform data modeling, SQL optimization, and performance tuning. Collaborate with cross-functional teams to understand data requirements and deliver robust solutions. Lead technical discussions, mentor junior engineers, and provide technical guidance. Implement best practices for data quality, security, and governance. Support CI/CD pipelines and follow version control best practices usingGitand automated deployments. Contribute to containerized deployments usingDocker/Kuberneteswhere applicable.Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 4+ years of hands-on experience inData Engineering . Strong expertise inPySpark, Databricks, and Apache Airflow . Solid hands-on experience withAWS cloud services . Strong proficiency inSQLand data performance tuning. Experience withCI/CD pipelines , version control (Git). Exposure toDocker and Kubernetesis an added advantage. Strong analytical, problem-solving, and communication skills. Ability to work effectively in a fast-paced, collaborative environment.



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