Icertis - Senior Software Engineer - Data Engineering

Job Summary : We are looking for a highly skilled Senior Software Engineer Data Engineering to design, build, and maintain scalable data platforms and pipelines that support business intelligence, analytics, and data-driven applications. The ideal candidate will have strong expertise in data engineering, software development, cloud technologies, and distributed data processing. Key Responsibilities : - Design, develop, and maintain scalable ETL/ELT data pipelines for structured and unstructured data. - Build reliable and high-performance data processing solutions using Python, SQL, Spark, or similar technologies. - Develop and maintain data platforms, data warehouses, and data lakes on cloud environments such as AWS, Azure, or GCP. - Integrate data from multiple sources including APIs, databases, applications, and third-party systems. - Ensure data quality, accuracy, availability, security, and governance across data pipelines. - Optimize data processing jobs and pipelines for performance, scalability, and cost efficiency. - Collaborate with Data Scientists, Analysts, Product Managers, and Software Engineers to deliver high-quality data solutions. - Implement monitoring, logging, testing, and alerting mechanisms for production data pipelines. - Contribute to architecture decisions, technical design, coding standards, and engineering best practices. - Participate in code reviews and mentor junior engineers while promoting a strong engineering culture. - Troubleshoot complex production issues and ensure timely resolution of data-related incidents. - Stay updated with emerging technologies in cloud data engineering, AI/ML platforms, data architecture, and distributed computing. Required Skills & Qualifications : - Bachelors degree in Computer Science, Engineering, Information Technology, or a related field. - 5 - 8 years of experience in software engineering/data engineering. - Strong proficiency in Python and SQL. - Hands-on experience with Apache Spark, Kafka, Airflow, or similar data engineering technologies. - Strong understanding of data warehousing, data lakes, ETL/ELT, and distributed systems. - Experience with cloud platforms such as AWS, Azure, or GCP. - Good understanding of relational and NoSQL databases. - Experience with Git, CI/CD, Docker, and modern software development practices. - Strong problem-solving, communication, and analytical skills.