Senior Database Architect

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

📋 Description

• Lead the development of data infrastructure that supports data-driven decision-making.

• Collaborate effectively 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 reliability, performance, and readiness for production.

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

• Construct and sustain scalable data systems that facilitate advanced analytics across the organization.

• Design frameworks for performance testing and release validation to avoid regressions.

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

⛳️ Requirements

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

• Over 5 years of experience as a Database Engineer, Data Engineer, or in a comparable role.

• Proven expertise 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.

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

• Skilled in building ELT pipelines utilizing dbt and Snowflake.

• Intermediate to advanced skills in Python development.

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

• Solid understanding of database internals and transactional systems.

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

• Knowledge of designing and implementing performance/load testing frameworks for data systems.

• Familiarity with benchmarking, regression testing, and release validation procedures.

• Experience in developing automated testing pipelines to ensure data quality and system performance across deployments.

• Capable of 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).

• Proficient with orchestration tools (Airflow).

• Experience with infrastructure-as-code (Terraform).

• Knowledge of the Software Development Lifecycle.

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

• Familiarity with containerization technologies (Docker, Kubernetes).

• Understanding of encryption, anonymization, and tokenization.

• Experience with open table formats and data catalogs.

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

🏝️ Benefits

• Competitive salary and comprehensive benefits package.

• Opportunities for professional development and career advancement.

• Flexible working hours and a supportive work environment.

• Access to cutting-edge technologies and tools.

• Collaborative and innovative company culture.