Data Architect
AUS - Wesley Place, Australia
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.
Our Team & Opportunity
Vanguard’s International division has a clear mission which is to change the way the world invests.
Our International Systems & Technology division has a compelling vision to enable superior client outcomes in International through engineering and operational excellence.
International Systems & Technology (IST) has defined strategy with four key strategic pillars: Deliver Business Value; Engineering Excellence; Engaged Crew & Data as a Strategic Asset.
The International Technology Office has Architecture teams that work with respective regional teams, particularly the Chief Data and Analytics Office (CDAO).
In this role, the Data Architect partners with teams in Vanguard to strategically advise on modern data architectures and AI.
Core Responsibilities
Design, implement, and review scalable data architectures to handle both streaming and batch processing pipelines to enable timely, up to real time, insights.
Collaborate with cross-functional teams to gather requirements and translate them into data solutions.
Develop and maintain data architecture blueprints.
Ensure data integrity, quality, and security throughout the data lifecycle.
Support modernisation efforts of data processing pipelines, including implementation and management of metadata-driven frameworks and engage with the toolset selection process
Design the workflow and pipeline architectures of ML and deep learning workloads.
Provide guidance on data science and advanced analytics architecture.
Advise on architectural trade-offs.
Collaborate effectively with data scientists, data engineers, data analysts, ML engineers, other architects, business unit leaders and CxOs (technical and nontechnical personnel), and harmonise the relationships among them.
Be a change agent to help the organization adopt data and AI-driven mindset. Take a pragmatic approach to the limitations and risks of AI, and project a realistic picture in front of IT executives who provide overall digital thought leadership.
What we are looking for
10+ years of experience in data architecture
Strong proficiency in handling very high velocity streaming data for building data lake/data warehouse solutions.
In-depth knowledge of components and architectural trade-offs involved across the data management, governance, model building, deployment and production workflows of AI is a must.
Software engineering and DevOps principles, including knowledge of DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD
Proficiency in AWS services , Apache Kafka (MSK), Cloud Formation, S3, Lambda, Step Functions, IAM, KMS, Athena, Glue, Glue Data Brew, EMR/Spark, Data Sync, Event Bridge, EC2, SQS, SNS, Lake Formation, Cloud Watch, Cloud Trail
Programming experience with advanced Python, SQL, PySpark.
Excellent problem-solving skills and the ability to articulate data architecture approach and decisions.
Previous hands one experience with data modelling techniques like Kimball, Data Vault v2 & 3NF
Experience in MLOps and productionising models architecture
Strong communication skills, both verbal and written, with the ability to present complex ideas clearly.
Specialisations that will make an impact
Working knowledge of the Financial Services Industry, in particular investment management, advice and superannuation.
Capability to question the status quo, challenge yourself and others to think out of the box on the value that will be delivered to our clients and advisers.
Familiarity with TOGAF, DAMA DMBoK will be advantageous
Proficiency with Databricks , Snowflake or GCP BigQuery
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: Architecture Athena AWS BigQuery CI/CD Databricks Data management Data warehouse Deep Learning DevOps DMBoK EC2 Engineering GCP Git Kafka Kubernetes Lake Formation Lambda Machine Learning MLOps Pipelines PySpark Python Security Snowflake Spark SQL Step Functions Streaming TOGAF
Perks/benefits: Career development
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