Overview
As a Digital Bank, data architecture, AI and engineering are at the core of what we do. Our architects and engineers operate in an autonomous environment where they are empowered to "do it right" and continuously learn, becoming masters in their craft. Leverage your extensive technical knowledge & people management skills to build, coach and inspire teams of Data and AI professionals. Use the latest cloud technologies, including Generative AI and Google Cloud, to tackle interesting banking and finance problems. Be part of a team that deeply values diversity and creates space for you to be your best.
At Macquarie, our advantage is bringing together diverse people and empowering them to shape all kinds of possibilities. We are a global financial services group operating in 31 markets and with 56 years of unbroken profitability. You'll be part of a friendly and supportive team where everyone - no matter what role - contributes ideas and drives outcomes.
What role will you play?
As a Senior Data Modeller, you'll harness your expertise in data modelling, architecture, engineering, and data management to take our Data strategy & ecosystem to the next level of maturity. You'll also be leading the definition of Conceptual, Logical and Physical data models aligned with business and technology strategy, while collaborating with business analysts, data engineers, lead engineers, business experts and group data architects
What you offer
* Expertise in data modelling in a variety of Big data environments in context of data warehousing cloud-based platforms (ideally with experience in AWS and GCP (Big Query preferred).
* Extensive experience as a data modeller or architect in a regulated environment that requires solutions for regulatory, finance, risk, Analytics and AI.
* Experience in establishing data architecture and data modelling related best practices, policies, standards and patterns to enhance productivity and quick decision making.
* Hands on experience in data modelling methodologies like Data Mesh, Inmon, Kimbal etc.
* Ability to work closely with Data Engineering leads from different teams simultaneously.
* Experience in solution design and integration patterns in context of data platforms.
* Experience in data governance, data management and data architecture practices
* Experience across full life cycle of large-scale data warehousing initiatives.
* Hands on experience in data modelling tools like Erwin with CI/CD.
* Automation and AI for innovative problem solving.
* Familiarity with Agile methodologies.
* Experience in banking and finance domain.
* Ability to work seamlessly with business and system SMEs, technical business analysts, product managers and senior stakeholders.
We love hearing from anyone inspired to build a better future with us, if you're excited about the role or working at Macquarie we encourage you to apply.
About Banking and Financial Services
Banking and Financial Services is our technology-driven retail bank. You will be part of a team that supports clients to achieve their full potential - whether that's buying a home, growing a business or investing to manage wealth.
Our commitment to diversity, equity and inclusion
We are committed to fostering a diverse, equitable and inclusive workplace. We encourage people from all backgrounds to apply and welcome all identities, including race, ethnicity, cultural identity, nationality, gender (including gender identity or expression), age, sexual orientation, marital or partnership status, parental, caregiving or family status, family and domestic violence status, neurodiversity, religion or belief, disability, or socio-economic background. We welcome further discussions on how you can feel included and belong at Macquarie as you progress through our recruitment process. To learn more, contact our team by clicking here .
Our aim is to provide reasonable adjustments to individuals who may need support during the recruitment process and through working arrangements. If you require additional assistance, please let us know in the application process.
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