Data Engineer

Overview

Data Engineer role at Vanguard Australia. Direct message the job poster from Vanguard Australia.

Talent Acquisition Specialist @ Vanguard Investments

About Vanguard

More than 45 years ago, John C. Bogle had a vision to start an investment company that did things differently. A company with no external shareholders. Where all the profits were invested back into the business and used to lower costs. Evidently, it was as bold as it was brilliant. To this day, Vanguard Group still has no external shareholders. That means no share prices to protect, and no profits to generate for outside owners.

Today, Vanguard is one of the world's largest investment management companies, serving more than 50 million investors worldwide. For more than 25 years Vanguard Australia has been supporting individual investors, financial advisers, and superannuation members to achieve their long-term financial goals.

Part of our growing Technology division, the CDAO team are responsible for transforming how our crew use data so that clients and investors can thrive. Our mission is to accelerate Vanguard's growth, clients, crew, and client experience by using data to inform and elevate every decision. We power information through data - improving outcomes, guiding strategies, and changing behaviour.

The Data Engineering team establishes technical excellence by knowing what their critical data is, where it is, and how it\'s being used. This supports Vanguard's reporting suite, global compliance, data quality, and data security efforts.

As a Data Engineer, you will report to the Data Engineering Manager and contribute to maintaining and building on the current AWS tech stack and involves building scalable, cloud-native data pipelines and services to support analytics and reporting across the APAC region. You will also contribute to the migration of our existing data lake infrastructure into a new Lakehouse environment, with a forward-looking roadmap that includes transitioning to a Modern data platform. You will also help define engineering standards and best practices, enabling a self-serve data ecosystem that empowers teams across the business.

What you will do

• Collaborate with Data Engineers and the Tech Lead to design, build, and roll out a metadata-driven, incrementally loading data platform on AWS.
• Build and maintain robust data pipelines using AWS services such as Step Functions, Lambda, and Glue. A deep understanding of these AWS services is essential.
• Support data quality and governance by writing maintainable, well-documented, and resilient code.
• Maintain and enhance existing infrastructure while working closely with the broader Data & Analytics team to ensure data is timely and accessible.
• Monitor, test, and report on current data lake processes, and help the Product Owner prioritise fixes or migrations to the new Lakehouse architecture.
• Be prepared to learn—or bring experience with—modern Lakehouse solutions such as Databricks, contributing to our future-state platform.
• Share your knowledge with the team through regular learning sessions and help uplift engineering capability across the crew.

What We Are Looking For

• Strong experience working in Cloud-based Engineering teams, preferably using AWS.
• Solid understanding of dimensional modelling, with Data Vault experience a bonus.
• Strong understanding of Python and SQL for data exploration and transformation, ideally within Spark environments (Pyspark, SparkSQL) such as within Glue jobs.
• Strong written and oral communication skills and presentation skills with the ability to translate business needs to system and software/data requirements.
• Strong analysis and analytical skills with attention to detail within complex systems and datasets, particularly on relationships between them.
• Solid understanding of version control systems, specifically Git.
• Experience working in Data & Analytics teams with Data Engineers, Analysts, Scientists on on-premises or cloud-based environments.
• Experience with or knowledge of working with SaaS products, CRM and ERP systems, and generally working with data in different formats, such as flat files, APIs, JSON, and RDBMS.
• Good understanding of lean and Agile principles, including Shift left, DevOps, CloudOps, DataOps, CI/CD & with a SRE mindset.
• Experience working in complex Data environments, including with ETL processes/data integration frameworks, such as with Data Lakehouses, Data Warehouses and Data Lakes.
• A self-starter who's comfortable with ambiguity and demonstrable learning agility.
• Experience with Data Visualization tools (Tableau is preferred) or business teams who used visualisation tools.

Specialisations that will make an impact

• Knowledge of the financial services industry, particularly Investment Management.
• Experience in setting up, operating, and monitoring a technical platform and its associated technologies.
• Capability to question the status quo, challenge yourself and the business on the value that will be delivered to our customers with clear justification for change.
• Lead issue resolution, identifying root cause and implementing solutions.
• Experience designing and building metadata-driven, incremental-load type warehouses on AWS.

Inclusion Statement

Vanguard's continued commitment to diversity and inclusion is firmly rooted in our culture. Every decision we make to best serve our clients, crew (internally employees are referred to as crew), and communities is guided by one simple statement: "Do the right thing."

We believe that a critical aspect of doing the right thing requires building diverse, inclusive, and highly effective teams of individuals who are as unique as the clients they serve. We empower our crew to contribute their distinct strengths to achieving Vanguard's core purpose through our values.

When all crew members feel valued and included, our ability to collaborate and innovate is amplified, and we are united in delivering on Vanguard's core purpose.

Our core purpose: To take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Information Technology

Note: All other location and salary postings have been omitted to maintain focus on the role and responsibilities.

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