Data Architect

Amtis Professional; Birmingham; On-site; GBP 76,000 - 90,000; Full time

Job summary

A leading data solutions provider in the UK is seeking a skilled Data Architect specializing in Azure and Databricks. The ideal candidate will design and deliver modern data solutions, optimize data platforms for advanced analytics, and ensure data quality and compliance. You will collaborate with data engineers and business stakeholders to translate requirements into scalable solutions. This is a permanent role with a competitive salary up to £90,000.

Qualifications

• Proven experience in designing and delivering data solutions in Azure.
• Expertise in architecting and optimizing Databricks environments.
• Strong understanding of data quality and governance principles.

Responsibilities

• Lead the design and architecture of data platforms using Azure services.
• Optimize Databricks environments for data engineering and analytics.
• Develop data models ensuring quality and governance.
• Collaborate with stakeholders to translate requirements into solutions.
• Oversee data integration and transformation pipelines.
• Ensure security and compliance in the data estate.

Skills

Azure Data Lake

Data Factory

Databricks

Data modeling

Data governance

Job description

Data Architect – Azure & Databricks

Permanent

Up to £90,000

Overview

We're looking for a Data Architect to design and deliver modern data solutions across an Azure ecosystem. You'll play a key role in shaping the data strategy, owning the architecture of scalable, secure, and high-performing data platforms that enable advanced analytics and business insights.

Key Responsibilities

• Lead the design and architecture of end-to-end data platforms using Azure services (e.g., Azure Data Lake, Data Factory, Synapse, Fabric, Key Vault).
• Architect and optimise Databricks environments for data engineering & analytics.
• Develop data models, standards, and best practices ensuring data quality, governance, and reliability.
• Collaborate with data engineers, analysts, and business stakeholders to translate requirements into scalable solutions.
• Oversee data integration, ingestion, and transformation pipelines across batch and streaming workloads.
• Ensure security, compliance, and cost optimisation throughout the data estate.