Data Engineer Job at City of London Full Time

We’re looking for a Data Engineer to join a fast-growing UK startup that’s reshaping how the hospitality industry manages staffing and operations through a data‑driven platform. You’ll play a key role in building the data foundations that power both internal decision‑making and customer‑facing products.

The role

You will be combining business analytics, data visualisation, data mining and data infrastructure to enrich data access across all business units and to enable data-driven decisions.

• Building and maintaining scalable data pipelines to support data integration into our customer-facing mobile and web-apps as well as internal dashboards
• Designing and implementing data architecture to optimize data storage, retrieval, and processing
• Developing ETL processes to ingest, transform, and load data from various sources, specifically APIs
• Collaborating with data scientists and software engineers to understand data needs for our customer-facing mobile and web-apps
• Working with internal stakeholders (e.g., Head of Ops, Head of Commercial) to understand and shape data requirements for internal data-driven decision making
• Creating and maintaining data documentation, monitoring pipeline performance, and troubleshooting issues

What you will have:

• Excellent problem-solving abilities demonstrated through academic or professional experience
• Strong foundations in data architecture, data engineering best practices, and scalable data solutions
• Solid understanding of data modeling techniques, database design, and data normalization
• Proficiency with Python and SQL, ideally with experience using data processing frameworks (e.g. Airflow, Tensorflow, Spark)
• Willingness to develop basic to intermediate proficiency in backend development (e.g., Python with Django) to support data pipeline integrations
• Familiarity with data versioning and data quality management practices
• Familiarity with build and deployment automation and CI/CD

Ideally:

• Some experience building and maintaining data pipelines in a production environment
• Experience with data lakes, warehousing, and other data storage patterns
• Proficiency with cloud platforms such as AWS or Azure, with experience using data services such as Apache Airflow, terraform or SageMaker