UST
Principal Data Engineer - Data Architect II
Nottingham
Posted 9 days ago
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Principal Data Engineer - Data Architect II
Principal Data Engineer
Location: Nottingham/London (Hybrid) Contract: Inside IR35/Permanent
About The Role
As a Principal Data Engineer, you will combine deep technical expertise with engineering leadership to drive the design, development, and evolution of our cloud-scale data platform. You will:
- Provide technical leadership across distributed data processing, data products, streaming architectures, and data platform capabilities
- Remain hands-on with coding, design, and engineering best practices
- Shape engineering standards, mentor teams, and influence technical direction
- Deliver robust, scalable data solutions enabling engineers, data scientists, analysts, and governance teams to unlock business value
Responsibilities
- Lead the design, development, and continuous evolution of cloud-scale data platforms and data products across batch and streaming workloads
- Act as a technical lead for complex data initiatives, providing guidance on solution design, engineering standards, and implementation approaches
- Design, build, and optimise distributed data processing pipelines using PySpark, Python, Airflow, and AWS services
- Drive engineering excellence through code reviews, technical coaching, design reviews, and adoption of software engineering best practices
- Partner closely with Product, Architecture, Cyber Security, Data Science, Analytics, and Governance teams to deliver scalable and reusable data capabilities
- Champion modern data engineering patterns, including:
- Data Lakehouse architectures
- ELT frameworks
- Data Products
- Event-driven processing
- Influence technology choices, engineering standards, and platform roadmaps while collaborating with Architecture and Enterprise Technology teams
- Improve platform reliability, scalability, observability, and operational excellence through automation, monitoring, and continuous improvement
- Drive adoption of:
- CI/CD
- Infrastructure-as-Code
- Testing strategies
- Engineering quality standards across the Data Engineering function
- Mentor and develop engineers, fostering a culture of:
- Technical excellence
- Continuous learning
- Innovation
- Support adoption of AI and ML platform capabilities by building trusted, scalable, and governed data foundations
- Contribute hands-on to the delivery of critical solutions, helping teams solve complex technical challenges and accelerate execution
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Requirements
- Significant experience as a:
- Lead Data Engineer
- Principal Data Engineer
- Technical Lead in a large-scale, data-driven organisation
- Strong hands-on software engineering expertise with:
- Python
- PySpark
- Apache Airflow
- Deep experience designing and building:
- Distributed data processing systems
- Large-scale data platforms on AWS
- Strong knowledge of modern AWS data technologies, including:
- Glue
- EMR
- Lambda
- DynamoDB
- S3
- EventBridge
- Step Functions
- Related services
- Proven experience building:
- Data Lakehouse platforms
- Data Products
- ELT/ETL frameworks supporting:
- Analytics
- ML
- AI workloads
- Expertise in streaming data architectures, event-driven systems, and real-time data processing patterns
- Strong understanding of:
- Data modeling
- Data quality
- Metadata management
- Governance
- Experience implementing:
- Software engineering best practices
- CI/CD pipelines
- Automated testing
- Infrastructure-as-Code
- Observability
- Demonstrated ability to:
- Lead technical delivery across multiple teams
- Influence engineering direction without direct authority
- Excellent stakeholder management and communication skills, including:
- Engagement across engineering teams
- Product teams
- Architecture teams
- Senior leadership teams
- Practical experience supporting:
- Machine Learning platforms
- Generative AI platforms
- Through scalable data engineering solutions
- Passion for:
- Mentoring engineers
- Building high-performing technical teams
- Strong problem-solving skills, balancing:
- Strategic thinking
- Hands-on execution
- Experience operating within:
- Regulated industries
- Ideally, Financial Services
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Skills
- Data architecture
- Data processing
- AWS Glue
- Cloud technology
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Skills
Data Architecture
Data Processing
AWS Glue
Cloud Technology
Python
PySpark
Apache Airflow
Data Lakehouse
ELT
ETL
Streaming Data
Event-Driven Systems
Machine Learning
Generative AI
CI/CD
Infrastructure-as-Code