Senior Analytics Engineer

AI Connect | Data & AI Delivery Partner; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Job summary

AI Connect | Data & AI Delivery Partner is seeking a Senior Analytics Engineer to join a newly formed Data Products capability in Private Banking & Wealth Management. You will design canonical data models and semantic layers to underpin analytics, AI, reporting and self-service capabilities across the bank.

Lead the development of trusted, governed data products and collaborate with data architects, analytics engineers and software engineers to shape a scalable cloud-based data platform.

Qualifications

• Proven experience as Analytics Engineer, BI Engineer or Data Architect in complex data environments.
• Strong experience designing Canonical Data Models across multiple business domains.
• Experience building Semantic Layers that expose trusted business metrics for reporting, dashboards and APIs.
• Excellent SQL and data modelling skills with modern cloud data platforms.

Responsibilities

• Design and develop canonical data models standardising core wealth entities across systems.
• Build semantic data models with consistent business definitions and metrics for dashboards, APIs and data products.
• Develop trusted, governed data products that are reusable and discoverable across the business.
• Collaborate with stakeholders to translate requirements into scalable data models.
• Work with Data Architects, Analytics Engineers and Software Engineers to shape the data platform.
• Implement data quality, governance controls and documentation to ensure accuracy and trust.
• Contribute to a scalable cloud-based data ecosystem enabling Analytics, AI and self-service reporting.

Skills

Analytics Engineer

BI Engineer

Data Architect

Canonical Data Models

Semantic Layers

SQL & Data Modelling

Stakeholder Management

Tools

Snowflake

dbt

Spark

AWS

Job description

London or Edinburgh (Hybrid)

AI Connect are partnering with a major UK bank to help them appoint a Senior Analytics Engineer to join a newly established Data Products capability within Private Banking & Wealth Management.

This is an exciting opportunity to help build the canonical and semantic data layers that underpin Analytics, AI, reporting and self-service capabilities across the business. You'll play a key role in creating trusted, reusable data products that enable faster, more consistent decision making across the organisation.

What You'll Do

• Design and develop canonical data models that standardise core wealth entities such as Accounts, Deposits and Customers across multiple systems.
• Build semantic data models that provide consistent business definitions and metrics for dashboards, APIs and downstream data products.
• Develop trusted, governed data products that are reusable, discoverable and consumed confidently across the business.
• Work closely with business stakeholders to understand requirements and translate them into scalable data models.
• Collaborate with Data Architects, Analytics Engineers and Software Engineers to shape the firm's next-generation data platform.
• Implement data quality standards, governance controls and documentation to ensure data remains accurate, trusted and compliant.
• Contribute to the design of a scalable cloud-based data ecosystem supporting Analytics, AI and self-service reporting.

Key Skills & Experience

• Proven experience as an Analytics Engineer, BI Engineer or Data Architect within complex data environments.
• Strong experience designing Canonical Data Models across multiple business domains.
• Experience building Semantic Layers that expose trusted business metrics for reporting, dashboards and APIs.
• Excellent SQL and data modelling skills with experience working on modern cloud data platforms.
• Hands-on experience with Snowflake, dbt, Spark and AWS.
• Experience building governed data products with strong data quality, documentation and ownership.
• Excellent stakeholder management skills with the ability to simplify complex technical concepts for business users.