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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Engineer - **Company:** Liberis - **Location:** London, UK - **Experience:** Expert - **Salary:** £60,000.0 - £88,000.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Artificial Intelligence, Airflow, Microsoft Azure, BigQuery, Software as a Service, Cloud Computing, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Migration, Database Queries, DevOps, Distributed Computing Environment, Python (Programming Language), SQL Azure, Cloud Services, Standard Sql, Azure Machine Learning, Data Streaming, Data Logging, Pulumi, Google Cloud, Snowflake, Cloudformation, Infrastructure Automation Frameworks, Apache Kafka, Machine Learning Operations, Terraform, Data Pipelines - **Published:** August 14, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5841744894 ## About the Role * Proven experience in data engineering roles, building and operating data pipelines at scale * Hands-on experience with Modern Data Stack architectures, including ingestion, warehouse, transformation, orchestration, and reverse ETL * Experience with tools such as DLT, Fivetran, or Airbyte for ingestion; BigQuery, Snowflake, or Redshift for warehousing; DBT for transformation; and Airflow or similar for orchestration * Strong Python programming skills, with the ability to write clean, testable, maintainable code with solid error handling and logging * Fluent SQL skills, including writing complex queries, understanding execution plans, and optimizing for performance and cost * Experience with cloud data platforms and distributed processing, including partitioning, cost optimization, and data governance * Experience with infrastructure-as-code tools such as Terraform, CloudFormation, or Pulumi, and deployment through CI/CD pipelines * Experience working in fast-moving environments where requirements evolve and reliability remains a priority * Understanding of DevOps principles, including observability, resilience, incident response, and operational excellence * Bonus experience with DLT or similar declarative ELT frameworks, Google Cloud Platform, Kafka, Pub/Sub, event streaming platforms, data quality frameworks, fintech, distributed teams, or legacy-to-modern data migration ## Description * Design, build, and maintain resilient data pipelines that ingest data from Azure SQL, SaaS platforms, and event streams into BigQuery * Write Python code using DLT to define declarative, testable, version-controlled pipelines * Build and operate ML feature pipelines that feed models with accurate, fresh features * Own the operational health of the systems we build, including monitoring, alerting, error handling, and incident response * Collaborate with analytics engineers to understand data needs, validate schema design, and establish data quality standards * Partner with the AI/ML platform team to design feature stores, streaming feature infrastructure, and model serving pipelines * Identify and execute optimisation work to improve performance, reliability, and developer velocity * Mentor junior engineers and support their career development * Participate in technical decisions about platform direction, infrastructure choices, tooling, and architecture trade-offs * Work cross-functionally with product teams, analytics engineers, BI specialists, and the ML platform team to shape data requirements and platform capabilities Technologies: * AI * Airflow * Redshift * Azure * BigQuery * CI/CD * Cloud * DevOps * ETL * Embedded * Fivetran * Support * Kafka * Model Serving * Pulumi * Python * SQL * Snowflake * Terraform * dbt * Business Intelligence * GCP ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Why segmenting your infrastructure into tiers makes your infrastructure design better](https://www.wearedevelopers.com/videos/1960-why-segmenting-your-infrastructure-into-tiers-makes-your-infrastructure-design-better) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Software Engineer Salary London](https://www.wearedevelopers.com/magazine/252-software-engineer-salary-london) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk)