Job Title

Job Title: Data Platform Support Engineer Department: Data Engineering / Technology Job Summary: We are seeking a skilled and proactive Data Platform Support Engineer to join our team. This role is critical in ensuring the smooth operation, maintenance, and enhancement of our data infrastructure and workflows. The ideal candidate will have hands-on experience with Airflow, Redshift, EMR, Python, SQL, and AWS, and will be responsible for monitoring, troubleshooting, and optimizing the data ecosystem. Key Responsibilities: Monitor and support data workflows built using Apache Airflow, including troubleshooting DAG failures and performance issues. Troubleshoot and resolve issues in AWS EMR clusters and Redshift data warehouse environments. Write and optimize SQL queries. Develop and maintain Python scripts for automation and housekeeping. Perform hands-on troubleshooting across the data ecosystem infrastructure, including compute, storage, and orchestration layers. Implement and maintain monitoring and alerting systems for data infrastructure such as Redshift, EMR, and Airflow using AWS cloud watch. Collaborate with engineers from cross teams to ensure platform availability. Participate in on-call rotations and provide timely support for production issues. Document processes, configurations, and troubleshooting steps for knowledge sharing. Required Skills & Qualifications: 3+ years of experience in data engineering or data platform support roles. Strong proficiency in Python and SQL. Hands-on experience with Apache Airflow, including DAG development and debugging. Experience with Amazon Redshift, AWS EMR, and other AWS services (e.g., S3, Lambda, CloudWatch). Proven experience in platform monitoring and hands-on troubleshooting in cloud-based data environments. Excellent problem-solving and communication skills. Ability to work independently and collaboratively in a fast-paced environment. Experience with CI/CD tools and practices. Familiarity with version control systems like Git. Preferred Qualifications: Familiarity with terraform. Exposure to big data technologies such as Spark or Hive.