Description

You will design, build, and maintain ETL/ELT pipelines and data models across PostgreSQL, MongoDB, and Amazon Redshift. This role owns the full lifecycle of data infrastructure, from pipeline development and database administration to performance optimization and security.

This role is hybrid.

Responsibilities

• Design and optimize data models and pipelines using AWS services including S3, Glue, Lambda, Step Functions, and Kinesis.
• Administer database environments across development, staging, and production, managing provisioning, upgrades, backups, and disaster recovery for RDS, MongoDB, and Redshift.
• Monitor data pipelines and databases, troubleshoot issues, implement alerts, and optimize query performance, indexes, and configurations.
• Ensure database security through access control, encryption, and role management, while defining and enforcing data retention and archival policies.
• Collaborate with analytics and product teams to support reporting needs, document processes, and participate in code reviews.

Required Skills

• 3–7 years of experience in data engineering or database administration.
• Strong proficiency with PostgreSQL, MongoDB, and Amazon Redshift.
• Solid SQL skills for both transactional and analytical workloads.
• Hands-on experience with AWS data services (S3, Glue, Lambda, RDS, Redshift).
• Proficiency in Python or another scripting language.
• Experience with workflow orchestration tools such as Airflow or Step Functions.
• Database administration skills including MongoDB replication/sharding, Redshift cluster management/WLM, and PostgreSQL replication/connection pooling.
• Familiarity with monitoring tools like CloudWatch, pgBadger, and MongoDB Atlas.
• Bachelor's degree in a relevant field.

Preferred Skills

• Experience with capacity planning and scaling systems to support growing data needs.

Key Skills

Education

Bachelor's degree