Data Engineer

What the role needs

• Design, build, and operate scalable data pipelines and data products across ingestion, transformation, storage, and production support.
• Develop and optimize data engineering solutions using Python and advanced SQL, with a focus on performance, cost efficiency, maintainability, and reliability.
• Build cloud-native data solutions using AWS, including technologies such as Glue, Redshift Serverless, Lambda, S3, Step Functions, SQS, and managed Airflow workflows.
• Develop data models, transformations, semantic models, KPI frameworks, and curated data layers that enable trusted analytics, AI, and self-service consumption.
• Implement and maintain CI/CD pipelines and Infrastructure as Code using GitHub Actions, Terraform, or comparable technologies.
• Embed data quality and governance practices, including lineage, quality controls, access management, and auditability, into data products and engineering solutions.
• Partner with product owners, business stakeholders, analytics teams, and architects to translate business requirements into scalable data products and actionable insights.
• Serve as a technical leader by mentoring data engineers, leading design and code reviews, establishing engineering best practices, and advancing engineering quality across the team.
• Participate in operational support, incident response, root cause analysis, monitoring, and continuous improvement to strengthen platform stability and reliability.
• Apply automation, AI-assisted engineering, and emerging AI/LLM and agentic AI patterns where appropriate to improve development efficiency, standardization, and solution reliability.
• 5 years of experience in data engineering, data analytics, programming, database administration, data management, or closely related technical work.
• Hands-on experience developing production data solutions using Python and advanced SQL.

From the employer

Vanguard is seeking an experienced Data Engineer to join the B2B AI and Data Engineering team. In this hands-on role, you will design, build, and operate scalable data pipelines and data products that support analytics, AI, and critical business functions. You will provide technical leadership, establish engineering standards, and partner with product, business, analytics, architecture, and security teams to deliver secure, reliable, and maintainable solutions. You will also contribute to modernization efforts by applying emerging AI and LLM capabilities where they create meaningful business or engineering value. Responsibilities: Design, build, and operate scalable data pipelines and data products across ingestion, transformation, storage, and production support. Develop and optimize data engineering solutions using Python and advanced SQL, with a focus on performance, cost efficiency, maintainability, and reliability. Build cloud-native data solutions using AWS, including technologies such as Glue, Redshift Serverless, Lambda, S3, Step Functions, SQS, and managed Airflow workflows. Develop data models, transformations, semantic models, KPI frameworks, and curated data layers that enable trusted analytics, AI, and self-service consumption. Implement and maintain CI/CD pipelines and Infrastructure as Code using GitHub Actions, Terraform, or comparable technologies. Embed data quality and governance practices, including lineage, quality controls, access management, and auditability, into data products and engineering solutions. Partner with product owners, business stakeholders, analytics teams, and architects to translate business requirements into scalable data products and actionable insights. Serve as a technical leader by mentoring data engineers, leading design and code reviews, establishing engineering best practices, and advancing engineering quality across the team. Participate in operational support, incident response, root cause analysis, monitoring, and continuous improvement to strengthen platform stability and reliability. Apply automation, AI-assisted engineering, and emerging AI/LLM and agentic AI patterns where appropriate to improve development efficiency, standardization, and solution reliability. Education & Experience: 5 years of experience in data engineering, data analytics, programming, database administration, data management, or closely related technical work. Hands-on experience developing production data solutions using Python and advanced SQL. Experience with AWS data engineering, including AWS Glue and cloud-native or serverless data architectures. Experience designing and supporting scalable data pipelines across ingestion, transformation, storage, and production operations. Experience with data modeling, transformation patterns, and analytics-ready data structures. Experience applying data quality and governance practices to production data solutions. Experience developing data products, semantic layers, or curated consumption models for analytics, reporting, or AI use cases. Experience implementing CI/CD and Infrastructure as Code using tools such as GitHub Actions, Terraform, or comparable technologies. Working knowledge of Apache Airflow or AWS-managed Airflow workflows. Undergraduate degree or an equivalent combination of training and experience. Experience with additional AWS services such as Redshift Serverless, Lambda, S3, Step Functions, and SQS, preferred. Experience with AI, agentic AI, Amazon Bedrock, knowledge graphs, Amazon Neptune, or related generative AI technologies and patterns, preferred. The intake identified these capabilities as advantageous while Python, advanced SQL, and AWS data engineering remain the core technical priorities. Special Factors Sponsorship Vanguard is not offering visa sponsorship for this position. About Vanguard At Vanguard, we don t just have a mission—we re on a mission. To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best. How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.