Description

What You’ll Do:

• Design, build and maintain ETL/ELT pipelines across multiple systems
• Design and optimize data models in PostgreSQL, MongoDB, and Amazon Redshift
• Develop and manage data workflows using AWS (S3, Glue, Lambda, Step Functions, Kinesis)
• Administer and maintain database environments across development, staging, and production
• Monitor data pipelines and databases, troubleshoot issues, and implement alerts
• Optimize query performance, indexes, and configurations across relational and NoSQL systems
• Manage database provisioning, upgrades, backups, and disaster recovery (RDS, MongoDB, Redshift)
• Ensure database security, including access control, encryption, and role management
• Plan capacity and scale systems to support growing data needs
• Define and enforce data retention and archival policies
• Collaborate with analytics and product teams to support reporting and data needs
• Document data pipelines, database processes, and operational procedures
• Participate in code reviews and follow engineering best practices

Core Skills & Experience:

• 3–7 years of experience in data engineering, database administration, or similar role
• Strong experience with PostgreSQL, MongoDB, and Amazon Redshift
• Solid SQL skills for both transactional and analytical workloads
• Experience with AWS data and database services (S3, Glue, Lambda, RDS, Redshift, etc.)
• Proficiency in Python or another scripting language
• Experience with workflow orchestration tools (Airflow, Step Functions, etc.)
• Hands-on database administration experience, including:
• MongoDB (replica sets, sharding, indexing, backups)
• Redshift (cluster management, query tuning, WLM, snapshots)
• PostgreSQL (replication, performance tuning, connection pooling)
• Familiarity with monitoring tools (CloudWatch, pgBadger, MongoDB Atlas, etc.)
• Understanding of database security (encryption, auditing, least-privilege access)

Key Skills

Education

Bachelor's degree