data engineer.

• Strong proficiency in programming languages such as Python, SQL, and R (experience with R is desirable).
• Proven experience working with relational database management systems and data warehousing architectures.
• Hands-on expertise using Git-based version control tools (e.g., GitHub, GitLab, Azure DevOps) within collaborative software development environments.
• Demonstrated experience operating effectively within Agile delivery frameworks.
• Background in designing and deploying cloud-native data architectures, with a preference for Google Cloud Platform (GCP).
• Proven track record of migrating legacy on-premises data platforms, pipelines, and services to cloud infrastructure.
• Solid grasp of data modeling concepts across conceptual, logical, and physical levels.
• Proven capability to design, construct, test, and maintain robust, scalable data pipelines and data products.
• Experience establishing CI/CD automation and streamlined deployment workflows.
• Experience leveraging container technologies such as Docker.
• Skilled in architecting and implementing robust ETL and ELT data pipelines.
• Familiarity with modern workflow orchestration frameworks (e.g., Airflow, Cloud Composer, Prefect, Dagster).
• Experience processing large-scale datasets using distributed computing engines (e.g., BigQuery, Spark, Dataproc).
• Proficiency in monitoring, troubleshooting, and optimizing platform performance and data pipelines.
• Solid understanding of DataOps and DevOps methodologies.
• Experience integrating systems via APIs and standard data integration techniques.

Data Architecture and Engineering Practices

• Understanding of how enterprise data platforms interoperate with broader organizational systems.
• Practical experience utilizing metadata management solutions, data lineage tools, and data catalogs.
• Experience implementing comprehensive data quality profiling, assessment, and validation frameworks.
• Demonstrated capability to design, develop, test, document, and support production-ready code and end-to-end data pipelines.
• Adept at leading code reviews and applying software engineering best practices, including unit testing, refactoring, and comprehensive technical documentation.

Governance, Compliance and Ethics

• In-depth understanding of information governance, data protection laws (including the Data Protection Act 2018 and UK GDPR), and secure data management standards.
• Awareness of ethical standards and considerations related to data processing and analytics.

Communication and Stakeholder Collaboration

• Strong interpersonal and communication skills for working effectively across cross-functional teams and engaging both technical and non-technical stakeholders.
• Proven skill in translating complex business requirements into scalable technical solutions and explaining technical details to non-technical audiences.

Qualifications & Experience

• Bachelor’s degree in Computer Science or a related quantitative field, or equivalent practical industry experience.
• Professional certification as a GCP Data Engineer or Cloud Architect is highly desirable., * written communication