Data Reliability Engineer

As a Data Reliability Engineer II, you will play a crucial role in developing, optimizing, and managing several large data lakes and data warehouses, comprising data from multiple disparate sources.

• Proactively monitor Postgre
  
  SQL RDS instances for performance, availability, and resource utilization (CPU, memory, storage, connections) using established monitoring tools (e.g., Cloud Watch, Prometheus).
• Assist in identifying performance bottlenecks in Postgre
  
  SQL RDS. Apply basic performance tuning techniques like reviewing query execution plans, adding missing indexes, and recommending parameter adjustments.
• Monitor the health and performance of Debezium and Kafka Connect connectors, identifying and troubleshooting basic issues related to data capture and delivery.
• Monitor ETL workflows and data pipelines for errors, performance bottlenecks, and processing delays. Troubleshoot and resolve issues to ensure reliable and timely data movement.
• Provide support for data related issues and participate in root cause analysis.
• Monitor the execution of Apache Airflow DAGs, identify failed tasks, and troubleshoot and re-run.
• Develop and maintain automation scripts and infrastructure as code (IaC) templates (e.g., using Crossplane, Terraform) to automate routine database tasks, deployments, and updates.
• Participate in on‑call rotations to respond to database‑related incidents and perform troubleshooting and root cause analysis.
• Assist in implementing and maintaining security best practices for cloud databases, including access controls, encryption, and compliance with regulatory requirements.
• Regularly audit and assess database security configurations.
• Configure and manage database backup and recovery strategies to ensure data integrity and availability in case of failures or data loss.
• Analyse database query performance and collaborate with developers to optimize SQL queries and schemas.
• Participate in continuous improvement initiatives to enhance the reliability, scalability, and performance of cloud databases.
• Assist in the design and optimization of database schemas for cloud environments.

• Familiarity with data pipeline concepts and technologies such as Debezium, Kafka Connect, and ETL frameworks.
• Basic understanding of Amazon Redshift and S3.
• Exposure to Apache Spark for data processing.
• Basic understanding of Apache Airflow for workflow orchestration.
• Strong SQL scripting skills for querying and basic data manipulation.
• Familiarity with scripting languages (e.g., Python, Bash) is a plus.
• Knowledge of database security best practices, including access controls, encryption, and compliance with regulatory requirements (e.g., GDPR, HIPAA).
• Having 'AWS Certified Database - Specialty' certification is a plus.

• Bachelor's degree in computer science, Information Technology, or a related field.
• 5-7 years of experience in database administration, with a focus on Postgre
  
  SQL.
• 2-4 years of hands‑on experience with Postgre
  
  SQL RDS.