Salary: £40,000 - 80,000 per year Requirements: 12-16 years of overall IT experience with significant data engineering & architecture exposure Strong Azure Cloud Data Engineering and associated services architecture knowledge Deep hands-on experience with Azure Data Factory (ADF) pipeline design, orchestration, integration runtime strategy SQL advanced querying, stored procedures, performance tuning Strong troubleshooting skills for complex multi-system data issues Strong understanding of data architecture concepts: Data lakes/lakehouse/warehouse, dimensional modeling, ELT/ETL patterns Experience in batch orchestration, dependency management, SCD handling, incremental loads Azure data services experience in one or more: Azure Synapse Analytics / Dedicated SQL Pools, Azure Databricks / Spark, ADLS Gen2, Azure SQL DB, Managed Instance, Event Hub / Kafka, Stream Analytics Strong documentation skills: architecture diagrams, solution designs, operational runbooks Excellent analytical thinking and structured problem-solving Strong communication and stakeholder management skills Ownership mindset, ability to drive standards and influence cross-team adoption Proven mentoring/coaching ability Bachelors/Masters degree in Computer Science, Information Systems, or related field (or equivalent experience) Responsibilities: Architect and design end-to-end Azure data engineering solutions (batch and near real-time) aligned to enterprise standards Define target state architecture for data ingestion, transformation, orchestration, and serving layers Lead architectural decisions around scalability, resiliency, performance, security, governance, and cost optimization Design, develop, test, and deploy Azure Data Factory pipelines following best practices (modular design, parameterization, reusability, CI/CD readiness) Build robust ingestion and orchestration workflows using Linked Services, Datasets, Pipelines, Triggers, Mapping Data Flows, and Integration Runtime strategies Implement operational excellence: logging, alerting, retry patterns, failure handling, and idempotent design Develop and optimize SQL queries and stored procedures to support ADF pipeline operations and downstream transformations Conduct query plan analysis and performance tuning (indexes, partitioning strategies, statistics, query rewrites) Establish SQL coding standards and reusable patterns for transformation logic Apply a strong analytical mindset to diagnose and resolve complex data integration issues across ingestion, transformation, orchestration, and storage layers Perform root cause analysis (RCA) for pipeline failures, performance degradation, data quality issues, and environment instability Design proactive monitoring dashboards and alerts for pipeline SLAs and data freshness Define and enforce best practices for CI/CD for ADF (Azure DevOps / Git-based workflows) Implement data governance patterns: metadata management, lineage, auditing, encryption, RBAC, key management, PII controls Collaborate with security/compliance teams to ensure enterprise adherence Act as a technical leader for data engineering squads; mentor and guide engineers on design patterns and implementation Translate business requirements into technical architecture and delivery plans Work closely with Product Owners, Data Analysts, Data Scientists, and Platform teams to ensure alignment Technologies: Architect Azure CI/CD Cloud Databricks DevOps ETL Git Support Kafka RBAC SQL Security Spark ARM More: We are seeking a strong Data Engineering Architect with 12-16 years of experience in building and architecting modern data platforms on Microsoft Azure. Our ideal candidate will have deep hands-on expertise in Azure Data Factory (ADF) pipeline engineering, SQL performance tuning, and end-to-end data integration architecture. In this role, you will lead solution architecture, define best practices, and mentor teams to build scalable, secure, and reliable data solutions. We value ownership and an analytical mindset, offering a collaborative environment where you can influence cross-team standards. Join us and be a part of a dynamic team focused on driving innovation in data engineering. last updated 11 week of 2026