Job Description
AECOM is seeking an experienced Data Engineer to play a key role in designing, delivering, and optimising data platforms and solutions across a wide range of projects.
As a Data Engineer, you will be responsible for delivering components of the data solution lifecycle, ensuring solutions adhere to standard quality metrics (scalability, security, resilience etc) and designing data-driven data architecture that serves value and delivers insight. Your work will directly support AECOM's mission to deliver innovative and sustainable solutions to our clients.
You will work closely with Data Analysts, Data Scientists, and cross-functional digital teams, supporting analytics use cases and occasionally contributing to light data-science activities such as feature engineering, exploratory analysis, or model operationalisation.
Key Responsibilities
- Develop concepts through the solution lifecycle, ensuring scalability and optimisation whilst considering cost.
- Oversee end-to-end data processes such as ingestion, transformation, modelling, and integration across multiple external facing projects.
- Demonstrate that solutions have met client performance, quality, security, and governance expectations.
- Collaborate with cross-functional data teams to gather client requirements.
Quality, Governance & Operational Excellence
- Work closely with Data Analysts and Data Scientists to support analytical projects providing support for work such as feature engineering, and big data-analysis activities.
- Collaborate with project managers, architects, and technical teams to ensure seamless integration of data solutions within wider digital ecosystems.
- Uphold data engineering best practices including code quality, testing, CI/CD, and documentation standards.
- Adhere to project data governance controls, including metadata management, access controls, data lineage, PII protection, and compliance with organisational and regulatory requirements.
- Develop monitoring and alerting strategies for data solutions, maintaining high availability, performance, and reliability.
- Troubleshoot complex issues across infrastructure, data solutions, and custom analytical products.
Innovation, Prototyping & Continuous Improvement
- Continuously explore new cloud capabilities, data platforms, and modern data stack tools to drive innovation within the team.
- Foster a culture of knowledge-sharing, standardisation, and collaborative team practices.
Qualifications
Minimum requirements:
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent professional experience).
- Professional experience designing and delivering cloud-based data engineering solutions at scale. Operating ETL/ELT pipelines and modern workflow orchestration tools (e.g., Apache Airflow, Azure Data Factory, Azure Functions)
- Advanced proficiency in at least one programming language commonly used in data engineering (Python preferred; Scala, Java, or C# also beneficial).
- Strong SQL skills and deep understanding of relational databases, non-relational stores, and data warehouse principles.
- Solid experience with data modelling methodologies (dimensional modelling, star/snowflake schemas, data vault, etc.).
- Strong grounding in analytical workflows and support for data-science activities (feature engineering, data preparation, exploratory analysis).
- Practical experience with CI/CD, version control (Git), testing frameworks, and DevOps practices.
We celebrate diversity, including neurodiversity, and believe it enriches our team. We welcome applications from all backgrounds and abilities. If you are an applicant with a disability that requires reasonable accommodation to complete the application process, please contact . At AECOM, we value everyone's unique contributions and perspectives.
All your information will be kept confidential according to EEO guidelines.