Data Warehouse Engineer

About Us Balfour Beatty is a leading international infrastructure group delivering complex projects worldwide. Our IT and Digital teams enable business transformation through innovative data platforms, advanced analytics, and enterprise solutions. About the Role We are seeking an experienced Senior Engineer to design, build, and maintain scalable data pipelines, models, and platforms.

This role plays a critical part in delivering high-quality, reliable data to support Analytics, Business Intelligence (BI), and AI/ML initiatives across the organization. Key Responsibilities Design, develop, and maintain scalable data pipelines across multiple source systems (ERP, CRM, APIs, files, event streams) Perform data ingestion, integration, and transformation to create clean, structured, and usable datasets Implement and maintain data quality frameworks including validation, completeness, and integrity checks Build optimized data models (Star schema, Lakehouse architecture) for reporting and analytics use Monitor and ensure data reliability, including pipeline performance, alerting, and failure handling Collaborate with data stewards, business users, and functional teams to troubleshoot and resolve data issues Implement data security controls including role-based access, row/column-level security, and classification Optimize ETL processes and improve performance and cost efficiency for analytics and AI workloads Support deployment pipelines using CI/CD practices and DevOps tools Maintain documentation, including ERDs, technical designs, and pipeline architecture Continuously enhance platform capabilities across AWS and MS Fabric ecosystems Technical Skills & Expertise Strong hands-on experience in data engineering and pipeline development Expertise in ETL tools: Azure Data Factory, AWS Glue, Informatica, Matillion, Databricks, MS Fabric Experience working with cloud platforms: AWS, Azure / MS Fabric, or similar Proficiency in SQL and data modelling techniques (Dimensional modelling, Data Warehousing) Experience with structured, semi-structured, and unstructured data Knowledge of data integration, APIs, and distributed data systems Familiarity with CI/CD tools and DevOps practices Hands-on exposure to performance tuning and optimisation Preferred / Desirable Skills Strong programming skills in Python / PySpark Experience with Databricks, Airflow, DBT Knowledge of Snowflake, Redshift, GCP data services Experience in building dashboards using Power BI Understanding of data governance, compliance, and security practices Experience handling large, complex datasets Exposure to AI/ML data pipelines Qualifications & Experience 6+ years of experience in Data Engineering / Data Platforms Proven experience in end-to-end data pipeline development and deployment Degree in Computer Science / Engineering / IT or equivalent experience Experience working in Agile / DevOps environments Behavioural Skills Strong problem-solving and analytical mindset Excellent communication skills with both technical and non-technical stakeholders Collaborative and team-oriented approach Ability to manage multiple priorities and deliver under pressure Detail-oriented with a focus on high-quality outcomes Proactive learning attitude and curiosity