Data Engineer, Analytics Engineering, VP
Data Engineer, Analytics Engineering, VP
NatWest Group15-17 Years
- Posted 3 hours ago
- Be among the first 10 applicants
Job Description
Join us as a Data Engineer, Analytics Engineering
As a Data Engineer, You'll need extensive experience in analytics engineering, data modelling and data strategy, with deep expertise in canonical modelling, semantic modelling, governed data products, Snowflake and modern analytics engineering practices. As a Principal Analytics Engineering Lead for PBWM, you'll provide strategic and technical leadership across the data and analytics landscape, defining standards, governance frameworks and best practices while shaping the analytical data strategy. You'll work closely with business stakeholders, architects, engineers, analysts and governance teams to design scalable, trusted and reusable data solutions that align with enterprise architecture and business objectives. You'll also enable self-service analytics, reporting, AI and advanced data products through robust canonical and semantic models that drive consistency, quality and business value across the organisation.
You'll act as a senior member of the Analytics Engineering team, bringing deep expertise in analytical data architecture, canonical and semantic data modelling, data product governance, and Analytics Engineering. You'll provide technical leadership across PBWM, partnering with senior business and technology stakeholders to align data capabilities with strategic objectives, drive enterprise data standards, and influence architecture and governance decisions. You'll lead the design and governance of complex cross-domain data models and trusted data products, establish DataOps and analytics engineering best practices including dbt, CI/CD, testing, lineage, and data quality frameworks, and champion reusable, product-based data delivery. You'll also mentor analytics engineers and data modellers, foster engineering excellence and innovation, and represent PBWM in enterprise architecture, governance, and data strategy forums while ensuring compliance with regulatory, privacy, and governance requirements.
Your Responsibilities Will Also Include
To thrive in this role, you'll need a strong understanding of data usage and dependencies and experience of extracting value and features from large scale data.You'll need at least fifteen years of experience in Analytics Engineering, Data Architecture, Data Modelling, Data Platform Engineering, or related disciplines, with deep expertise in canonical and semantic data modelling, data product design, metadata management, lineage, governance frameworks, and product-oriented architectures. You'll bring expert SQL skills and advanced hands-on experience with dbt, including models, macros, testing frameworks, documentation, lineage, CI/CD integration, and enterprise-scale project delivery.
You'll need extensive experience with Snowflake, covering architecture, performance tuning, cost optimisation, data governance, security, Cortex, and emerging platform capabilities, alongside a strong understanding of cloud-native analytical platforms on AWS, including S3, Glue, Athena, Iceberg, IAM, security controls, and governance, with SageMaker Unified Studio preferred. Experience within Financial Services, ideally Personal Banking & Wealth Management (PBWM), will be advantageous, along with knowledge of PBWM products and customer journeys, DAMA/DMBOK or similar governance frameworks, and UK regulatory requirements covering GDPR, data privacy, retention obligations, conduct, suitability, regulatory reporting, and audit controls.
Additionally, You'll Need
- You'll be the voice of our customers, using data to tell their stories and put them at the heart of all decision-making
- We'll look to you to drive the build of effortless, digital first customer experiences
- If you're ready for a new challenge and want to make a far-reaching impact through your work, this could be the opportunity you're looking for
- We're offering this role at vice president level
As a Data Engineer, You'll need extensive experience in analytics engineering, data modelling and data strategy, with deep expertise in canonical modelling, semantic modelling, governed data products, Snowflake and modern analytics engineering practices. As a Principal Analytics Engineering Lead for PBWM, you'll provide strategic and technical leadership across the data and analytics landscape, defining standards, governance frameworks and best practices while shaping the analytical data strategy. You'll work closely with business stakeholders, architects, engineers, analysts and governance teams to design scalable, trusted and reusable data solutions that align with enterprise architecture and business objectives. You'll also enable self-service analytics, reporting, AI and advanced data products through robust canonical and semantic models that drive consistency, quality and business value across the organisation.
You'll act as a senior member of the Analytics Engineering team, bringing deep expertise in analytical data architecture, canonical and semantic data modelling, data product governance, and Analytics Engineering. You'll provide technical leadership across PBWM, partnering with senior business and technology stakeholders to align data capabilities with strategic objectives, drive enterprise data standards, and influence architecture and governance decisions. You'll lead the design and governance of complex cross-domain data models and trusted data products, establish DataOps and analytics engineering best practices including dbt, CI/CD, testing, lineage, and data quality frameworks, and champion reusable, product-based data delivery. You'll also mentor analytics engineers and data modellers, foster engineering excellence and innovation, and represent PBWM in enterprise architecture, governance, and data strategy forums while ensuring compliance with regulatory, privacy, and governance requirements.
Your Responsibilities Will Also Include
- Building advanced automation of data engineering pipelines through removal of manual stages
- Embedding new data techniques into our business through role modelling, training, and experiment design oversight
- Delivering a clear understanding of data platform costs to meet your departments cost saving and income targets
- Sourcing new data using the most appropriate tooling for the situation
- Developing solutions for streaming data ingestion and transformations in line with our streaming strategy
To thrive in this role, you'll need a strong understanding of data usage and dependencies and experience of extracting value and features from large scale data.You'll need at least fifteen years of experience in Analytics Engineering, Data Architecture, Data Modelling, Data Platform Engineering, or related disciplines, with deep expertise in canonical and semantic data modelling, data product design, metadata management, lineage, governance frameworks, and product-oriented architectures. You'll bring expert SQL skills and advanced hands-on experience with dbt, including models, macros, testing frameworks, documentation, lineage, CI/CD integration, and enterprise-scale project delivery.
You'll need extensive experience with Snowflake, covering architecture, performance tuning, cost optimisation, data governance, security, Cortex, and emerging platform capabilities, alongside a strong understanding of cloud-native analytical platforms on AWS, including S3, Glue, Athena, Iceberg, IAM, security controls, and governance, with SageMaker Unified Studio preferred. Experience within Financial Services, ideally Personal Banking & Wealth Management (PBWM), will be advantageous, along with knowledge of PBWM products and customer journeys, DAMA/DMBOK or similar governance frameworks, and UK regulatory requirements covering GDPR, data privacy, retention obligations, conduct, suitability, regulatory reporting, and audit controls.
Additionally, You'll Need
- Experience of ETL technical design, data quality testing, cleansing and monitoring, data sourcing, and exploration and analysis
- Data warehousing and data modelling capabilities
- A good understanding of modern code development practices
- Experience of working in a governed, and regulatory environment
- Strong communication skills with the ability to proactively engage and manage a wide range of stakeholders
More Info
Key Skills
cloud-native analytical platforms
semantic modelling
Unified Studio
governed data products
data quality frameworks
ETL technical design
data quality testing
canonical modelling
CI CD
Iceberg
SageMaker
analytics engineering
Athena
IAM security controls




