Data Engineer

You will develop and maintain raw, curated, and business-ready data models within Snowflake, ensuring data is structured, documented, and optimised for analytics and self-service reporting. You will support the delivery of trusted datasets and semantic layers that power downstream analytics and enable scalable, data-driven decision-making across the organisation.

Platform Optimisation & Continuous Improvement

You will help improve the reliability, scalability, performance, and observability of the modern data platform, identifying opportunities to optimise Snowflake usage, streamline workflows, improve automation, and enhance developer experience as TLC’s data capabilities continue to evolve.

Cross-Functional Collaboration

You will work closely with Analysts, Technology, Product, and Client teams to understand data requirements and deliver scalable data solutions that support business decision-making.

Operational System Integration

You will support integrations across TLC’s operational ecosystem, including COSMOS, Mixpanel, external plugins, and third-party platforms, helping ensure reliable, accurate, and scalable movement of data across business systems.

Data Quality, Governance & Engineering Best Practices

You will contribute to data governance, testing, monitoring, documentation, and engineering standards to ensure trusted, high-quality datasets and scalable development practices across the data platform. This includes version control, code reviews, automation, and continuous improvement of engineering processes.

What we're looking for:

• Proven experience in data engineering, analytics engineering, or modern data platform development

• Strong SQL and Python skills, with experience building and optimising data transformations, automation, and scalable data workflows

• Experience working with cloud data warehouses such as Snowflake, BigQuery, Redshift, or similar, including performance, scalability, and cost optimisation

• Understanding of dimensional modelling, semantic layer design, and building curated business-ready datasets for analytics and reporting

• Experience developing and maintaining ELT/ETL pipelines, including ingesting and integrating data from APIs, SaaS platforms, and operational systems

• Experience monitoring and troubleshooting data pipelines, schema changes, synchronisation issues, and platform reliability

• Familiarity with modern data stack tools such as Fivetran, dbt, orchestration tools, Git, and collaborative engineering practices including version control and code reviews

• Experience working with cloud platforms such as Azure and/or GCP

• Strong communication skills with the ability to work across technical and non-technical stakeholders

• A proactive mindset with an interest in modern data platform trends, AI enablement, automation, scalability, and continuous improvement

Preferred Experience

• Experience with Snowflake optimisation and performance tuning

• Experience working with event analytics platforms such as Mixpanel

• Familiarity with modern analytics platforms

• Experience using Python for data engineering or automation tasks

• Familiarity with customer, campaign, loyalty, or martech data ecosystems

• Experience working with AI/GenAI capabilities within Snowflake, including implementing best practices and leveraging advanced analytics and machine learning features to support business use cases.