At a Glance
- Tasks: Build and maintain scalable data pipelines using modern cloud-native tools.
- Company: Join a dynamic tech team in the heart of Manchester.
- Benefits: Competitive salary, annual bonus, private healthcare, and 28 days leave.
- Other info: Collaborative environment with regular team events and hackathons.
- Why this job: Tackle complex data challenges and make a real impact on analytics and ML systems.
- Qualifications: 3+ years in data engineering, strong Python and SQL skills required.
The predicted salary is between 60000 - 80000 £ per year.
Build and maintain scalable data pipelines and infrastructure.
About the Role
As a Data Engineer, you'll be the backbone of our data infrastructure, designing and maintaining the pipelines that power our analytics and ML systems.
You'll work with modern cloud-native tools to ensure our clients' data flows are robust, secure, and optimised for performance.
This role is ideal for engineers who love solving complex data challenges at scale and take pride in building systems that 'just work'.
- Design and build scalable ETL/ELT pipelines using Apache Spark and Airflow
- Architect data lake and data warehouse solutions on AWS, GCP, or Azure
- Implement data quality frameworks with automated testing and monitoring
- Optimise query performance across large-scale analytical workloads
- Collaborate with ML engineers to build and maintain feature stores
- Ensure data security, governance, and compliance (GDPR, SOC 2)
- Document data models, lineage, and pipeline architectures
Requirements
- 3+ years of experience in data engineering or backend development
- Strong proficiency in Python and SQL
- Experience with Apache Spark, Airflow, or similar distributed processing frameworks
- Hands‑on experience with cloud data services (Redshift, Big Query, Snowflake, or Databricks)
- Understanding of data modelling (dimensional, data vault) and warehousing patterns
- Familiarity with infrastructure‑as‑code (Terraform, Cloud Formation)
- Experience with version control and CI/CD practices
- Nice to Have
Experience with streaming data (Kafka, Kinesis, Flink) Knowledge of dbt for data transformation Familiarity with containerisation (Docker, Kubernetes) Experience building feature stores for ML workloads AWS/GCP/Azure data engineering certifications
- Competitive salary with annual bonus
- £1,500 annual learning and certification budget
- Private healthcare and dental cover
- On‑site role at our modern Manchester city centre office
- 28 days annual leave plus bank holidays
- Pension matching up to 6%
- Regular team events and quarterly hackathons
- About the Team
Our Data Engineering team of 6 engineers builds the foundational infrastructure that powers everything we do.
We're passionate about clean architecture, automated testing, and building systems that scale gracefully.
We work closely with analytics and ML teams to ensure data flows seamlessly from source to insight.
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