Sr. Database Architect

As a Senior Database Engineer, you will drive data infrastructure that enables data-informed decision-making, applying modern engineering and distributed systems practices. You will partner closely with Product Managers, Data Analysts, Software Engineers, and business stakeholders to deliver stable, high-quality data pipelines, enterprise reporting, and datasets that support analytics and machine learning use cases.

A primary responsibility of this role is to optimize and maintain our OLTP databases, ensuring reliability, performance, and production readiness. This includes auditing systems, improving data quality, refactoring legacy pipelines, and applying best practices for schema design, indexing, and query performance. In parallel, you will build and maintain scalable data systems that power advanced analytics across the business.

You will design performance testing and release validation frameworks to prevent regressions and ensure data integrity, while establishing strong production processes such as monitoring, alerting, backup and recovery, access controls, and incident response.

What You Need (Required Knowledge, Skills & Abilities)

Education & Experience

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)

Who You Are (Soft Skills)

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

£55,000 - £75,000 a year

We are proud to offer competitive salary ranges aligned to industry standards. Please note that our ranges are representative and individual compensation specifics may vary based upon experience level, professional competencies and geographic differentials.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.