About this role
Responsibilities:
• Design, build, and maintain scalable ETL/ELT pipelines for critical IT data sources • Develop curated, high-quality datasets to support reporting, dashboards, and analytics products • Write, optimize, and maintain SQL and Python code for transformation, automation, and performance • Deliver cloud-based data solutions using AWS services such as Glue, S3, and Athena • Partner with analysts, product managers, and stakeholders to translate data needs into practical solutions • Implement data quality checks, validation rules, monitoring, and documentation to ensure trusted data • Troubleshoot pipeline issues, investigate anomalies, and resolve data defects end-to-end • Apply engineering best practices including version control (Git), code reviews, testing, and CI/CD deployment • Contribute to standards for data lineage, governance, documentation, and production support • Support the evolution of reusable data products and self-service analytics capabilities Education & Experience:
• Bachelor’s degree or equivalent combination of education and relevant experience • 3–5+ years of experience in data engineering, analytics engineering, or data platform development • Strong proficiency in SQL and Python for data transformation and automation • Hands-on experience building and supporting ETL/ELT pipelines • Experience with AWS or similar cloud data platforms • Solid understanding of data modeling, curated datasets, and BI/reporting use cases • Demonstrated problem-solving skills and commitment to data quality and reliability • Ability to communicate effectively with both technical and non-technical stakeholders • Experience working in collaborative, agile team environments Preferred:
• Experience with AWS Glue, PySpark, Athena, Dremio, Parquet • Exposure to BI and visualization tools such as Tableau, Power BI, or Streamlit • Familiarity with Jira, GitHub, ServiceNow, or technology operations data • Interest in building reusable data products and enabling self-service analytics • Exposure to AI/ML concepts, LLMs, or agent-based tools to enhance data engineering workflows and automation 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.