
Data Engineer
- Barton-upon-Humber, Lincolnshire
- Permanent
- Full-time
- Assist in building and maintaining data pipelines, ensuring efficient data ingestion, transformation, and processing.
- Monitor data performance, security, and availability using tools like Datadog or CloudWatch.
- Implement automated testing for ETL workflows to ensure data quality and consistency.
- Support senior engineers in optimising data models and transformations for analytics and reporting.
- Contribute to data governance efforts by following best practices for data security, access control, and documentation.
- Work closely with analysts and business stakeholders to understand data requirements and deliver well-structured data solutions.
- Design, build, and optimise data pipelines and infrastructure to support training and fine tuning of LLMs, collaborate with data scientists and ML engineers to manage and serve datasets, and integrate AI models into production systems to power intelligent customer facing features.
- Participate in code reviews, knowledge-sharing sessions, and collaborative problem solving within the team. Maintain and update technical documentation, including data lineage and architectural diagrams. Stay up-to-date with emerging trends and technologies in data engineering, proactively applying relevant innovations
- Regular social events
- Staff discount on purchasing a kitchen after 1 year of continuous employment
- Free annual eye tests as well as a contribution to new glasses
- Quarterly bonus scheme
- 2+ years of experience in data engineering, with hands-on experience in building ETL/ELT pipelines.
- Proficiency in Python for data wrangling and automation.
- Experience working with cloud-based data platforms (AWS, Azure, or GCP).
- Familiarity with data lake architectures and modern ETL tools (e.g., Databricks, Snowflake, AWS Glue).
- Strong problem-solving skills and attention to detail in data quality and documentation.
- Use of SQL for querying and transforming structured data.
- Ability to collaborate effectively with technical and non-technical stakeholders.
- Experience using monitoring tools such as Datadog or CloudWatch for observability and troubleshooting.
- Familiarity with BI tools such as Power BI or Tableau for reporting and data visualisation.
- Experience working in Agile development environments (e.g., using Jira for task tracking).
- Exposure to data governance principles, including access control and data security best practices.
- Experience working with LLMs to drive business insight.
- Understanding of CI/CD pipelines and automated testing frameworks for data engineering.
- Knowledge of SQL for querying and transforming structured data