Data Engineer

Description:

Commonwealth Bank

To empower our people and the communities in which we work and making sustainable, transparent and balanced business decisions.

We really love working here, and we think you will too. Diversity, flexibility and innovation are just some of the reasons why our people come to work every day.

Our team includes around 45,000 people from all walks of life, with different goals, experiences, and perspectives. At CommBank we’ll encourage and support you to be yourself. This is a place where you can feel confident expressing who you really are; where you belong because of your uniqueness.

Do work that matters: The Chief Data and Analytics Office(CDAO) is in place to realise a data-driven organisation for Commonwealth Bank Group. We do this by solving complex problems around data for the business and activating data for strategic and sustained competitive advantage to enhance the financial wellbeing of our customers in a safe, sound and secure way.

As a Data Engineer you’ll be part of the Data Engineering Advanced Analytics Chapter.

You will join a team of engineers who go above and beyond to improve the standard of digital banking. Using the latest tech to solve our customers’ most complex data-centric problems. To us, data is everything. It is what powers our cutting-edge features and it’s the reason we can provide seamless experiences for millions of customers from app to branch.

We’re responsible for CommBank’s key analytics capabilities and work to create world-leading capabilities for analytics, information management and decisioning.

We are seeking people who have:

• A passion for building next generation data platforms across the bank
• Ability to execute state-of-the-art coding practices, driving high quality outcomes to solve core business objectives and minimise risks
• Excellent communication and collaboration skills: Ability to effectively communicate technical concepts to both technical and non-technical audiences.
• Experience with Generative AI models: Working knowledge of leading large language models (LLMs) and their applications.
• Data Engineering Skills: Experience with data pipelines, data extraction, transformation, and loading (ETL) processes.
• A natural drive to educate, communicate and positively influence a large stakeholder group

Tech skills: We use a broad range of tools, languages, and frameworks. We don’t expect you to know them all but experience or exposure with some of these (or equivalents) will set you up for success in this team

• Strong foundation in computer science fundamentals: Data structures, algorithms, object-oriented programming, and software design principles.
• Proficiency in Python: Excellent knowledge of Python programming language and its libraries (e.g., NumPy, Pandas, Scikit-learn).
• AI Agentic Framework: Proficiency in using leading agentic framework LangGraph, lamaindex, crew ai, autogen, RAG, and Vector Databases(weaviate, OpenSearch) within an AI development context.
• AWS Platform: Experience with AWS services such as EC2, S3, Lambda, SageMaker, and other relevant AI/ML
• Data Engineering Skills: Experience with data pipelines, data extraction, transformation, and loading (ETL) processes.

Nice to have:

• Experience with containerisation technologies like Docker and Kubernetes.
• Experience with MLOps practices, including model training, deployment, and monitoring.
• Experience with graph databases (e.g., Neo4j) or knowledge graph technologies.

• Data Cleaning and Preparation

  Extract and clean data ready to use in analysis or to users

• Data Analysis and Reporting

  Analyze data to discover and communicate insights, and offer concrete recommendations for key stakeholders to make critical decisions

• SQL and Databases

  Use SQL to query databases to extract and process data

• Learning agility

  Identifies and applies strategies to enhance reception, retention and use of newly acquired information, skills, and abilities

• Numerical problem solving

  Works with numerical information and performs mathematical calculations to solve problems

• Attention to detail

  Accurately identifies and rectifies discrepancies or errors that exists in information and deliverables