Senior Database Architect

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Drive the data infrastructure that supports data-driven decision-making.

• Collaborate closely with Product Managers, Data Analysts, Software Engineers, and business stakeholders.

• Provide stable, high-quality data pipelines, enterprise reporting, and datasets.

• Optimize and maintain OLTP databases, ensuring they are reliable, performant, and production-ready.

• Conduct system audits, enhance data quality, refactor outdated pipelines, and implement best practices.

• Develop and sustain scalable data systems that facilitate advanced analytics throughout the organization.

• Create performance testing and release validation frameworks to avert regressions.

• Establish robust production processes, including monitoring, alerting, backup and recovery, access controls, and incident response.

⛳️ Requirements

• Bachelor's degree in Mathematics, Statistics, Computer Science, or a related field.

• Over 5 years of experience as a Database Engineer, Data Engineer, or in a similar capacity.

• Proven experience in designing, implementing, and maintaining high-performance, scalable OLTP systems.

• Proficient hands-on experience and advanced knowledge of SQL (e.g., Postgres, Snowflake).

• Strong background in data modeling, data warehouses, and lakehouse architectures.

• Expertise in designing and implementing scalable data architectures, including both batch and streaming pipelines.

• Experience in building ELT pipelines utilizing dbt and Snowflake.

• Intermediate to advanced skills in Python development.

• Proven experience in assessing and enhancing existing database systems, including performance tuning (indexing, query optimization, partitioning) and data quality improvement.

• Strong understanding of database internals and transactional systems.

• Experience in implementing backup, recovery, and high-availability strategies.

• Skilled in designing and implementing performance/load testing frameworks for data systems.

• Knowledgeable in benchmarking, regression testing, and release validation processes.

• Experienced in constructing automated testing pipelines to ensure data quality and system performance across deployments.

• Skilled in defining and maintaining production database processes, including monitoring, alerting, and incident response.

• Familiar with observability tools and practices (logging, metrics, tracing).

• Strong grasp of SLAs, SLOs, and best practices for data reliability.

• Proficient with AWS data technologies (Glue, Kinesis, Lambda).

• Experienced with orchestration tools (Airflow).

• Knowledgeable in infrastructure-as-code practices (Terraform).

• Familiarity with the Software Development Lifecycle.

• Experienced with CI/CD pipelines, particularly for data systems.

• Knowledgeable in containerization technologies (Docker, Kubernetes).

• Understanding of encryption, anonymization, and tokenization principles.

• Experienced with open table formats and data catalogs.

• Familiar with data observability tools (e.g., Monte Carlo, Datadog, Prometheus).

🏝️ Benefits

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and remote work options.

• Opportunities for professional development and training.

• Generous paid time off and holiday policies.

• Collaborative and inclusive work environment.