Data Engineer

Cloud Bridge; Newcastle upon Tyne; On-site; GBP 120,000 - 150,000; Full time

Benefits offered by this job

Enhanced annual leave

Enhanced sick pay

Enhanced maternity benefits

Personalised development plans

Structured training and development

Paid social events

Cycle to Work scheme

Job summary

Cloud Bridge is seeking a Senior Data Engineer to lead the design and construction of a cloud-based data platform that powers analytics and AI capabilities across the organization.

You will own data structuring, governance, and strategy, collaborating with the CTO to shape data and AI initiatives, from enterprise reporting to cutting-edge AI solutions. This is a hands-on leadership role with a focus on scalable, secure, and cost-efficient data architectures.

Qualifications

• Proven experience in a senior Data Engineering, Data Architecture, or Lead Data role.
• Hands-on design and delivery of cloud-based data platforms.
• Expertise with AWS Redshift, Glue, S3; Azure Synapse, Data Factory, Azure SQL; Databricks; Snowflake.
• Strong data modelling experience across enterprise-scale environments.
• Knowledge of Retrieval-Augmented Generation (RAG), vector databases, embeddings, and LLM integrations.
• Experience with batch and streaming/real-time data processing.
• Strong governance, quality management, lineage, and metadata frameworks.
• Excellent stakeholder engagement and communication skills.

Responsibilities

• Design and build scalable, cloud-based data platforms and architectures.
• Translate business requirements into robust, scalable data solutions.
• Develop conceptual, logical, and physical data models.
• Design and implement modern AI-ready architectures, including RAG, vector databases, semantic search, and LLM integrations.
• Build and optimise data pipelines supporting both batch and real-time processing.
• Lead data integration, transformation, and migration initiatives.
• Establish and maintain data governance, data quality, metadata management, and security frameworks.
• Collaborate with engineering, architecture, and business stakeholders to deliver impactful solutions.
• Evaluate emerging technologies and recommend innovative approaches to enhance data and AI capabilities.
• Provide technical leadership, best practice guidance, and mentoring across data initiatives.
• Ensure data platforms are scalable, secure, cost-effective, and aligned to business objectives.
• Define the organisation's data and AI strategy from the ground up.
• Work directly with senior leadership and influence business-critical decisions.
• Build solutions using the latest cloud, data, and AI technologies.
• Drive architectural decisions and implement best practices.
• Access tailored development plans, training, and certification support.
• Join a business actively investing in transformation and AI adoption.

Skills

AWS Redshift

AWS Glue

AWS S3

Azure Synapse

Azure Data Factory

Azure SQL

Databricks

Snowflake

Data modelling

LLM integrations

RAG

Job description

Our client are seeking an experienced Senior Data Engineer to play a pivotal role in designing and building the data platform that will power the organisation's next generation of analytics and AI capabilities. This is a hands‑on leadership role where you will take ownership of how data is structured, governed, and leveraged across the business. You will be responsible for defining the strategic direction of the data platform while actively contributing to its design, development, and implementation. Working closely with senior stakeholders, including the CTO, you will help shape the organisation's data and AI strategy, enabling everything from enterprise reporting and advanced analytics to cutting‑edge AI and machine learning solutions.

Responsibilities

• Design and build scalable, cloud-based data platforms and architectures.
• Translate business requirements into robust, scalable data solutions.
• Develop conceptual, logical, and physical data models.
• Design and implement modern AI-ready architectures, including RAG, vector databases, semantic search, and LLM integrations.
• Build and optimise data pipelines supporting both batch and real-time processing.
• Lead data integration, transformation, and migration initiatives.
• Establish and maintain data governance, data quality, metadata management, and security frameworks.
• Collaborate with engineering, architecture, and business stakeholders to deliver impactful solutions.
• Evaluate emerging technologies and recommend innovative approaches to enhance data and AI capabilities.
• Provide technical leadership, best practice guidance, and mentoring across data initiatives.
• Ensure data platforms are scalable, secure, cost-effective, and aligned to business objectives.
• Define the organisation's data and AI strategy from the ground up.
• Work directly with senior leadership and influence business-critical decisions.
• Build solutions using the latest cloud, data, and AI technologies.
• Drive architectural decisions and implement best practices.
• Access tailored development plans, training, and certification support.
• Join a business actively investing in transformation and AI adoption.

Benefits

• Enhanced annual leave plus birthday leave
• Enhanced sick pay
• Enhanced maternity benefits
• Personalised development plans
• Structured training and development programmes
• Paid social events
• Cycle to Work scheme

As part of Cloud Bridge, an AWS Premier Partner, we bring deep cloud expertise into every hiring conversation. Here, technology meets empathy - connecting the dots between ground-breaking companies and exceptional talent.

Essential

• Proven experience in a senior Data Engineering, Data Architecture, or Lead Data role.
• Strong hands‑on experience designing and delivering cloud-based data platforms.
• Expertise with one or more of the following technologies:
  • AWS (Redshift, Glue, S3, Bedrock)
  • Microsoft Azure (Synapse, Data Factory, Azure SQL)
  • Databricks (Delta Lake, ETL pipelines, ML workloads)
  • Snowflake
• Strong data modelling experience across enterprise-scale environments.
• Experience building modern AI-enabled data architectures.
• Knowledge of Retrieval-Augmented Generation (RAG), vector databases, embeddings, and LLM integrations.
• Experience with both batch and streaming/real-time data processing.
• Strong understanding of data governance, quality management, lineage, and metadata frameworks.
• Excellent stakeholder engagement and communication skills with the ability to translate complex technical concepts into business outcomes.

Desirable

• Experience within Financial Services, Professional Services, or Advisory environments.
• Knowledge of FinOps, cloud cost optimisation, and total cost of ownership considerations.
• Relevant cloud and data certifications.
• Exposure to MLOps and AI platform engineering.