Senior Data Engineer

Description

The company runs a team that builds the data and machine learning products behind customer experience, marketing performance and commercial decisions.

In this senior role on the Customer and Marketing Machine Learning team, you will help lay the data groundwork for machine learning models, pricing optimisation, customer analytics, media measurement and marketing decisions at scale.

The team combines Data Engineers, Machine Learning Engineers and Applied Scientists to deliver end-to-end machine learning products with clear business impact.

You will work with very large customer, marketing and commercial datasets to build sound data solutions that help the company understand, reach and serve millions of customers.

Responsibilities

• Build scalable pipelines that feed machine learning, analytics and data science work.
• Build high-performance data solutions with Python, Spark, Databricks and Azure.
• Create and maintain datasets for customer, marketing, pricing and forecasting use cases.
• Work with Applied Scientists and Machine Learning Engineers to get models running in production.
• Design data models and architectures that keep data reliable, trusted and easy to access.
• Raise data quality, observability, lineage and monitoring across key data products.
• Support media measurement, customer value, pricing and personalisation work.
• Tune processing workloads for speed, scale and cost.
• Set standards for software engineering, data engineering and platform development.
• Lead technical direction through design reviews, mentoring and knowledge sharing.
• Partner with Customer, Marketing and Commercial stakeholders to turn business problems into scalable data solutions.
• Shape the long-term direction of the company's machine learning and data capabilities.

Requirements

• The company is looking for people who meet many of these points, and you are encouraged to apply even if you do not match every one.
• Significant experience delivering data engineering solutions in cloud environments.
• Strong Python skills and experience building production-grade data pipelines and data products.
• Hands-on experience with Databricks, Spark and distributed processing.
• Experience designing and running large-scale data platforms on Azure, AWS or GCP.
• Deep understanding of data modelling, data architecture and modern data engineering principles.
• Experience building data infrastructure that supports data science, analytics or machine learning.
• Solid knowledge of CI/CD, Infrastructure as Code, automated testing and observability.
• Experience with large customer, marketing, commercial or behavioural datasets.
• A track record of leading complex technical solutions from concept through to production.
• Experience mentoring engineers and shaping technical direction in a team.
• Strong stakeholder management and communication skills for both technical and non-technical audiences.
• Enjoy tackling hard data problems and helping teams make better decisions with data.
• Experience supporting machine learning platforms, MLOps or model operationalisation.
• Experience with pricing, marketing analytics, recommendation systems or customer analytics.
• Experience in eCommerce, retail or consumer-facing digital businesses.

Conditions

If you need adjustments during the process, you can tell the talent team at any point, in whatever way suits you.

Benefits

• Employee discount on purchases.
• Access to employee sample sales.
• 25 days of paid annual leave plus an extra day to celebrate a special moment.
• Discretionary bonus scheme.
• Private medical care scheme.
• Flexible benefits allowance that you can take as extra cash or spend on other benefits.
• Opportunities for personalised learning and in-the-moment development to help you thrive in the role.