Principal Data Engineer - AWS

About the role

Principal Data Engineer – AWS

Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent

Engineer future-ready data platforms that power financial transformation.

The Role

We’re looking for a Principal Data Engineer with AWS to join our growing team of engineering experts driving next-generation transformation for Tier 1 financial services clients. You’ll play a pivotal role in designing, building, and deploying cloud-based data pipelines that enable trusted, scalable data platforms. Working across greenfield initiatives and enterprise-scale programmes, your work will directly influence how data is ingested, transformed, and consumed across the financial services industry. You'll also embrace AI-enabled ways of working, using approved AI and automation tools where appropriate to enhance productivity, improve delivery quality, and accelerate engineering outcomes while applying sound engineering judgement and responsible AI practices.

What You’ll Do

- Design and build end-to-end data pipelines using AWS-native services and modern cloud data architectures, ensuring scalable, secure, and resilient solutions.

- Partner with clients and cross-functional teams to understand business requirements, define technical solutions, and deliver production-grade data platforms.

- Apply AWS Well-Architected Principles, engineering best practices, CI/CD, and AI-enabled development approaches to improve quality, efficiency, and operational excellence.

- Lead the development of robust, tested, fault-tolerant data engineering solutions while promoting responsible engineering standards and governance.

- Mentor engineers, share technical expertise, and encourage the effective and responsible use of approved AI tools and automation to enhance collaboration and delivery.

What We’re Looking For

- Strong proficiency in Python, Scala, or Java, with hands-on experience of Big Data technologies including Spark, Hadoop, or similar distributed processing frameworks.

- Experience building real-time event streaming solutions using technologies such as Kafka, Spark Streaming, or Amazon Kinesis within AWS environments.

- Proven expertise designing modern data architectures including Data Lakehouse and Data Warehousing solutions, alongside CI/CD, DevOps practices, and data governance including GDPR.

- A collaborative engineering mindset with experience delivering scalable cloud solutions and using AI-enabled tools responsibly to improve engineering productivity while maintaining appropriate human oversight and quality assurance.

- Excellent stakeholder communication skills with the ability to translate business requirements into practical, high-quality technical solutions.

Bonus Points For

- Expertise in data modelling, schema design, and working with structured and semi-structured datasets.

- Experience with distributed technologies including Hadoop, Spark, HDFS, Hive, Databricks, or AWS Lake Formation.