DataOps Engineer

As a DataOps Engineer with 03 years of experience, you will be an integral part of our dynamic data engineering team, contributing to the development and maintenance of scalable and efficient data pipelines and workflows using modern data platforms and cloud-native tools. Your primary responsibilities will include designing, building, and optimizing robust data pipelines utilizing technologies such as Databricks, PySpark, and Kafka. You will also be involved in creating ETL/ELT workflows for large-scale data processing, integrating data systems with orchestration engines like Camunda, and ensuring data quality and observability practices are in place for pipeline reliability. Collaboration with data scientists, analysts, and business stakeholders will be essential as you work towards providing actionable insights and supporting data-driven decision-making across the organization. Additionally, your role will involve working with real-time analytics solutions using tools like Apache Druid and assisting in maintaining CI/CD pipelines and DevOps practices for data systems. To excel in this role, you should possess a solid understanding of Python programming, hands-on experience with PySpark, and familiarity with cloud-based data pipeline development. Proficiency in stream processing tools like Apache Kafka, working knowledge of SQL, and experience with data orchestration tools such as Camunda or Airflow are also required. Strong communication skills and the ability to work both independently and collaboratively in a team environment are vital for success in this position. While experience with Apache Druid, cloud platforms like Azure, and knowledge of DevOps practices and Agile software development environments are preferred, they are not mandatory. We offer a comprehensive benefits package, including medical insurance for employees and their families, a hybrid work culture, promoting work-life balance, a friendly working environment, and certification reimbursement based on project demands. Join us in driving data-driven innovation and growth within our organization.,