Database Architect

A primary responsibility of this role is to optimize and maintain our high-volume OLTP databases, with a strong emphasis on PostgreSQL. You will assess existing environments, identify performance and scalability bottlenecks, and drive improvements across schema design, indexing, partitioning, query performance, replication, and database configuration. You will also provide guidance to engineering teams as they design and implement new database-backed features.

You will help strengthen production readiness by establishing and improving practices around performance testing, release validation, monitoring, alerting, backup and recovery, high availability, access controls, and incident response. You will play a key role in troubleshooting complex production issues, performing root-cause analysis, and ensuring database changes are thoroughly tested before deployment.

This role requires someone who can combine deep hands-on database expertise with strong technical judgment and communication skills and someone who can assess an existing environment, make practical recommendations, and partner with engineering teams to implement scalable, reliable solutions.

• Bachelor’s degree in Mathematics, Statistics, Computer Science, or related field

• 5+ years of experience as a Database Engineer, Data Engineer, or similar role Core Data Engineering & Architecture

• Experience designing, implementing, and maintaining high performant, scalable OLTP systems.
• Hands-on experience and advanced knowledge of SQL (e.g., Postgres, Snowflake)
• Strong experience with data modeling, data warehouses, and lakehouse architectures
• Experience designing and implementing scalable data architectures, including batch and streaming pipelines
• Experience building ELT pipelines with dbt and Snowflake

• Intermediate to advanced Python development skills Database Optimization & Reliability

• Experience assessing and improving existing database systems, including performance tuning (indexing, query optimization, partitioning) and data quality remediation
• Strong understanding of database internals and transactional systems

• Experience implementing backup, recovery, and high-availability strategies Performance Testing & Release Validation

• Experience designing and implementing performance/load testing frameworks for data systems
• Knowledge of benchmarking, regression testing, and release validation processes

• Experience building automated testing pipelines to ensure data quality and system performance across deployments Production Operations & Data Reliability

• Experience defining and maintaining production database processes, including monitoring, alerting, and incident response
• Familiarity with observability tools and practices (logging, metrics, tracing)

• Strong understanding of SLAs, SLOs, and data reliability best practices Tools & Platforms

• Experience with AWS data technologies (Glue, Kinesis, Lambda)
• Experience with orchestration tools (Airflow)
• Experience with infrastructure-as-code (Terraform)
• Knowledge of the Software Development Lifecycle

Preferred Skills & Experience:

• Experience with CI/CD pipelines, especially for data systems
• Experience with containerization (Docker, Kubernetes)
• Knowledge of encryption, anonymization, and tokenization
• Experience with open table formats and data catalogs
• Familiarity with data observability tools (e.g., Monte Carlo, Datadog, Prometheus), * Detail-oriented, with a strong data quality mindset
• Strong problem-solving and troubleshooting skills with a proactive approach to system reliability
• Self-starter with a bias toward ownership and continuous improvement
• Comfortable bringing structure and best practices to ambiguous or legacy environments
• Thrives in a fast-paced, startup-oriented, team-focused culture
• Positive, collaborative, and energetic attitude
• Excellent verbal and written communication skills
• Ability to clearly explain complex technical issues to both technical and non-technical audiences