About this role

Develop applications and data pipelines using PostgreSQL, Python and AWS
Design, develop, and maintain PostgreSQL database architecture for enterprise backend applications
Lead schema design, database migrations, versioning, and ensure backward compatibility
Optimize SQL queries, indexing strategies, execution plans, and overall database performance
Assist in identifying performance bottlenecks in PostgreSQL RDS
Apply basic performance tuning techniques like reviewing query execution plans, adding missing indexes, and recommending parameter adjustments
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
Configure and manage database backup and recovery strategies to ensure data integrity and availability in case of failures or data loss
Analyze 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

Bachelor's degree in computer science, Information Technology, or a related field
5-8 years of experience in data Engineering, with a focus on AWS Glue, Python and PostgreSQL
2-4 years of hands-on experience with PostgreSQL RDS
Familiarity with data pipeline concepts and technologies such as Kafka Connect, and ETL frameworks
Strong understanding of Amazon Glue, 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 data manipulation
Strong experience with scripting languages (e.g., Python, Bash)
Having ‘AWS Certified Database
Specialty’ certification is a plus.

Database Engineer

Key skills