Data Engineer

Job Summary

The Data Engineer plays an important role in the development of our software solution, used by our clients to help them with their complex data transformation challenges. Our system combines the latest ML based techniques with logic-based transformation, overseen by domain experts, to provide innovative solutions to our clients. This role supports the development of the data system focusing on orchestration, resilience and scaling.

Additionally, we aim to provide a framework on which our data transformation modules can be developed by a growing team of junior engineers and technical SMEs. The role may also support the implementation of the systems, including deployment and integration with clients’ own data stores, processes and workflows.

Data Hub is a dynamic team of scientists and developers who love solving complex problems. We provide leading edge technology solutions and services to solve our clients’ data transformation and analytics challenges across a range of industries including geothermal, environmental, hydrocarbon and mineral exploration. You will be working in an open and collaborative environment with opportunities to learn, grow, and develop.

We have an informal team culture and believe work should be fun and rewarding. You will be based in Llandudno, North Wales in a hybrid setting, and you will be working alongside our teams of data engineers, machine learning engineers, software engineers and subject matter experts.

• Plan, develop, deploy and maintain connectors and integrations between our data system and clients systems, such as systems of record or downstream consumption channels.
• Contribute to the development of our data platform infrastructure, including orchestration systems, data processing logic and interactions between system components.
• Help develop a flexible framework for data transformations by creating a modular system where new transformation logic can be easily developed and integrated into our product offering.
• Build and maintain robust data pipelines with a focus on dynamic, end-to-end, metadata driven solutions that consider a wide range of implications, such as downstream application/UI data access patterns, maintainability, monitoring, access control etc.
• Influence our choice of architecture and technology.
• Communicate design ideas and solutions clearly through architectural diagrams and documentation to both technical and non-technical stakeholders.
• Apply best practices in software and data engineering, writing secure, performant, and maintainable code (Python, SQL), minimizing technical debt and optimizing performance where it matters.
• Partner with data analysts, data scientists, and other end‑users to understand their requirements and ensure the platform and its data are accessible, reliable, and meet project delivery needs.
• Share work and best practices; collaborate with others; ensure alignment to company growth ambitions.

• Essential experience developing data integrations with geoscience or other scientific data types, particularly in oil and gas and/or mining domains.
• Previous experience designing, building and maintaining data transformations in a system or product setting.
• Ability to write secure and performant code in Python and SQL, and to optimize queries and data pipelines.
• Experience using orchestrators and ETL tools, especially Airflow.
• Significant RDBMS experience (Postgre
  
  SQL, Oracle).
• Experience with other database types such as No
  
  SQL database (e.g. Neo4j, Elastic) or vector.
• Data architecture experience relating to data modelling, data warehousing and schema design (3NF, dimensional modelling, medallion architecture).
• Experience with Docker, VCS (git, Gitlab) and knowledge of CI/CD.
• Enthusiastic attitude towards learning and ability to adapt to new challenges or changes in direction.
• Preferred:
  Knowledge of Dev Ops and Data Ops best practices.
• Preferred:
  Kubernetes deployment experience.
• Preferred:
  Microsoft Azure and cloud native data technologies, e.g. Azure Data Factory, Databricks.
• RESTful API / Graph
  
  QL.
• Infrastructure as Code.
• Previous experience building web applications…