Senior Data Engineer
AUS - Wesley Place
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.
Our team & opportunity:
Part of our growing Technology division, the Chief Data Analytics Office (CDAO) team is 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.
As a Senior Data Engineer, you will be reporting into the Data Engineering Manager and will be focussed on a green-field project to design, instantiate, and roll out a brand-new Data Lakehouse solution across the APAC region and beyond, as well as managing, supporting, and migrating the existing data lake infrastructure to the new world.
You’ll play a key role in defining the standards for our new data store and guiding the Engineering team to build a modern solution that enables self-serve data. You'll have experience leading a large team, prioritising effort, and focussing effort strategically and tactically.
What you will do
Work with our Engineers and Tech Lead to design, build, and roll out a metadata-driven, incrementally loading data lakehouse solution on AWS.
Support Data Quality and Data Governance processes by writing maintainable, well-documented, and resilient code.
Support existing infrastructure and processes working closely with the wider Data & Analytics team to ensure accessible and timely data.
Monitor, test, and report on the current data lake processes and work with the Product Owner to appropriately prioritise correction or migration to the new lakehouse.
Contribute to the learning and development of our existing crew, providing knowledge share sessions to ensure we’re all along for the ride.
Support the leadership and management of the Data Engineering team.
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.
Thorough 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.
Experience leading teams, prioritising effort, and focussing effort strategically and tactically
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.
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile APIs AWS CI/CD Data Analytics Data governance DataOps Data quality Data visualization DevOps Engineering ETL Git JSON PySpark Python RDBMS Spark SQL Tableau
Perks/benefits: Career development Salary bonus
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