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Greater London, England, United Kingdom
Hybrid
As the Senior Database Architect, you will provide technical leadership for the design, performance, scalability, and reliability of our production database environments. You will partner closely with Software Engineers, Platform Engineers, Product Managers, and other technical stakeholders to evaluate existing database architectures, identify opportunities for improvement, and establish database engineering best practices across our products.
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.
5+ years of experience as a Database Engineer, Data Engineer, or similar role
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
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
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
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
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
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