Data Engineer - London OR Manchester - £70k - £90k - AI/ML SaaS
Location: London OR Manchester
Reporting to: Head of Data Science
Employment Type: Full-time
About the Role:
We are seeking a skilled Data Engineer to play a critical role in building, optimising, and maintaining robust data infrastructure and scalable data pipelines that power machine learning, MLOps, analytics, and product intelligence.
This role is responsible for building reliable, scalable, and observable production-grade data systems with clearly defined SLAs, data freshness guarantees, and monitoring standards. You will design and operate both batch and streaming pipelines that produce reliable, ML-ready datasets for product, analytics, and inference use cases.
You will own end-to-end data pipeline development, the design of clean and well-governed data assets that accelerate ML development, and the reliability, observability, and cost-efficiency of the platform in production.
Key Responsibilities:
- Own the development and optimisation of batch and streaming data pipelines that reliably ingest and transform high-volume clickstream and external data.
- Lead the implementation and performance optimisation of a multi-node, TB-scale Redshift data warehouse , including data modelling, storage design, and cost-efficient query performance.
- Deliver curated, versioned, ML-ready data assets , ensuring consistency, usability, and alignment with downstream use cases.
- Own pipeline reliability by defining SLAs , ensuring data freshness, and implementing monitoring, data quality validation, observability, alerting, and structured incident response processes.
- Implement and operationalise feature computation workflows , including the development and maintenance of feature store infrastructure, to support model training and inference in collaboration with Data Science and Platform teams.
- Drive improvements in platform scalability, resilience, and cost efficiency across the data ecosystem.
Requirements:
- Proven track record of building and operating production-grade data pipelines and data warehouse solutions in high-scale environments.
- Demonstrated ownership of pipeline reliability, SLAs, monitoring, and incident debugging in production systems.
- Deep proficiency in Python and SQL , with experience working on large-scale event data.
- Strong hands-on experience with AWS data infrastructure , including services such as:
- S3
- Redshift
- Glue
- Kinesis
- Lambda
- Experience in performance and cost optimisation of cloud-based data systems.
- Experience building streaming and event-driven data pipelines (e.g. Kinesis or equivalent technologies).
Desirable / Nice to Have:
- Experience in high-volume event data environments , such as adtech, fraud detection, or cybersecurity.
- Experience collaborating closely with infrastructure or platform teams.
- Familiarity with infrastructure-as-code tools , such as Terraform.
- Understanding of security and compliance-aware environments , including:
- SOC 2
- ISO standards
- IAM best practices
- data classification frameworks
What Success Looks Like:
Within the first 6–12 months , success in this role would include:
- Reliable, production-grade data pipelines operating at scale with clear SLAs, strong data quality guarantees, and minimal operational overhead.
- Meaningful improvements to data warehouse performance and cost efficiency through improved data modelling, query optimisation, and workload management in Amazon Redshift.
- Successful support of machine learning workflows , including robust feature computation pipelines that enable faster and more reliable model development and deployment.
- Strong ownership of data reliability, demonstrated through effective monitoring, fast debugging, and well-managed production incidents.
- Clear documentation, trusted datasets, and strong adoption from downstream stakeholders.
Why Join:
- Play a central role in shaping the data architecture of a scaling ML-driven product environment
- High ownership and strong technical influence
- Direct product and commercial impact
- Competitive salary and benefits package
- Flexible working options
- Supportive, inclusive, and collaborative culture
We are committed to building a diverse and inclusive team and strongly encourage applications from individuals from backgrounds traditionally underrepresented in technology.
If you are excited about this opportunity but do not meet every requirement, we would still love to hear from you.