Mid-Senior Data Engineer | £85,000 – £110,000 + Bonus | Hybrid, London
Retelligence are partnering with a data-driven organization in London to hire a Mid-Senior Data Engineer into a growing data function. This is a hands-on role for someone who has worked across the whole data lifecycle, from ingestion through to modelled, analytics-ready data, and wants real ownership of how the platform is designed and built.
The Package
- Annual bonus with a generous multiplier scheme
- Permanent position (contractors looking to move into a permanent role are very welcome to apply)
- Hybrid working from a London office
The Role
You'll be involved in every part of data engineering, not just one corner of it. That includes:
- Designing, building and maintaining reliable batch and streaming pipelines from a wide range of internal and external sources
- Developing and optimizing the cloud data warehouse, making sure it is performant, cost-efficient and scalable
- Shaping the data architecture, including layered approaches such as medallion (bronze, silver, gold) and lakehouse patterns
- Data modelling for analytics and reporting, using dimensional / Kimball-style models, star schemas and well-structured transformation layers
- Orchestrating workflows and building in monitoring, alerting, testing and data quality checks - Applying engineering best practice through version control, CI/CD, infrastructure as code and code review
- Working closely with analysts, data scientists and business stakeholders to turn requirements into trusted data products
- Contributing to technical decisions and helping to raise standards across the team
What We're Looking For
- Proven end-to-end data engineering experience covering pipelines, warehousing, architecture and modelling
- Strong Python for building and maintaining data pipelines and tooling
- Strong, advanced SQL, including performance tuning and complex transformations
- Hands‑on experience with a modern cloud data warehouse, ideally BigQuery (Snowflake, Redshift, Synapse or Databricks also considered)
- Experience with orchestration and transformation tools such as Airflow / Cloud Composer, Dagster, dbt or Dataform
- Familiarity with ingestion and processing tools such as Pub/Sub, Kafka, Dataflow / Apache Beam or Spark
- Cloud experience, ideally including GCP. Multi‑cloud backgrounds are welcome, so if most of your experience is on AWS and/or Azure with some GCP exposure, we’d still love to hear from you - Experience with Git, CI/CD and infrastructure as code (e.g. Terraform)
- A clear communicator who can explain technical trade‑offs to non-technical stakeholders
Nice to Have
- Data governance, cataloguing and lineage tooling
- Docker and containerised workloads
- Experience mentoring or supporting more junior engineers