Staff Data Engineer

Organization: At CommBank, we never lose sight of the role we play in other people’s financial wellbeing. Our focus is to help people and businesses move forward to progress. To make the right financial decisions and achieve their dreams, targets, and aspirations. Regardless of where you work within our organisation, your initiative, talent, ideas, and energy all contribute to the impact that we can make with our work. Together we can achieve great things.

Job Title: Staff Data Engineer
Location: Bangalore-Manyata Tech Park

Business & Team: Business Banking - EBB

We're building tomorrow’s bank today, which means we need creative and diverse engineers to help us redefine what customers expect from a bank. Envisioning new technologies that are still waiting to be invented and reimagining products that support our customers and help build Australia’s future economy.

CommBank is recognised as leading the industry in IT and operations with its world-class platforms and processes, agile IT infrastructure, and innovation in everything from payments to internet banking and mobile apps. Our Software team are the brains behind Australia’s number one banking app, Netbank, Cardless Cash, Comm Sec Pocket and Spend Tracker. We go beyond a passion for web and mobile development, creating reliable APIs at a unique scale in Australia. And you could be a part of that journey.

Impact & Contribution:

The CBA technology unit delivers the best digital banking services to Commonwealth Bank customers and to do so is responsible for digital delivery, group data and analytics, technology and technology infrastructure, cyber, fraud, physical security and business resilience for all divisions across CBA. It is also dedicated to delivering the best workplace technology experience for our over 53.000 people across CBA and focused on providing the latest tools, technology, and resources to enhance the way we work together and empower our people to achieve more for our customers.

As Staff Data Engineers at CBA provide deep technical leadership by designing and governing scalable, secure data platforms that power enterprise analytics, real‑time data, and AI use cases. They act as force multipliers—setting engineering standards, mentoring teams, and shaping data architecture to ensure trusted, future‑ready data foundations aligned to the bank’s strategic priorities.

Your role will report into the Engineering Manager under EBB

Roles & Responsibilities:

• Understand customers’ core business objectives and translate them into robust, end-to-end data-centric solutions that deliver measurable business outcomes.

• Lead the definition, design and execution of data engineering and ETL strategies, including data staging, architecture, integration patterns and internal and external application interfaces.

• Design and develop highly reliable, secure and scalable data pipelines, platforms and data products, with comprehensive test coverage and strong engineering practices.

• Design technical solutions and data consumption patterns for complex business requirements, ensuring solutions are robust, secure, highly available and aligned with architectural and engineering standards.

• Participate across the full lifecycle of agile delivery, from ideation and planning through implementation, ensuring technical deliveries align with engineering direction, strategy and approved delivery frameworks.

• Partner with business, operational, infrastructure, product and engineering teams to improve the scalability and reliability of services while ensuring compliance with organisational guidelines, requirements and industry standards.

• Provide data engineering expertise and technical leadership across platforms, products and delivery teams, influencing stakeholders and guiding strategic data programs and technology decisions.

• Drive engineering maturity and continuous improvement through reusable frameworks, tooling, automation and improvements to engineering and delivery practices.

• Provide thought leadership, mentorship and capability uplift across engineering teams, contributing to knowledge sharing through technical discussions, documentation and engineering communities.

• Take ownership of nominated technical assets, roadmaps and technical direction, and participate in On-Call rosters from time to time to resolve critical issues and ensure the reliable operation of systems, products and platforms.

Essential 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:

• 10+ years of experience in design or development in Analytics and Data Warehousing projects.

• Experience in building end-to-end solutions with the Big data platform, Spark or scala programming, Apache Flink, and Kafka for real-time and batch data.

• Experience in AWS ways of designing and building reliable and scalable data pipelines in AWS cloud Ecosystem.

• Solid experience in ETL pipeline building with spark or scala programming framework with knowledge in developing UNIX Shell Script, Oracle SQL/ PL-SQL.

• Strong in Python/Pyspark for data manipulation, API integration, and automation, alongside Scala.

• Experience in building AI/GenAI powered engineering applications is highly recommended.

• Experience in utilizing GenAI framework (Lang chain, Llama, Hugging Face) and automation applications is highly desirable.

• Experience with Oracle SQL database programming, SQL performance tuning, and relational model analysis.

• Experience in Advanced SQL for optimizing complex queries, combined with sophisticated data modeling (dimensional modeling for cloud warehouses).

• Extensive experience with Teradata data warehouses and Cloudera Hadoop. Proficient across Enterprise Analytics/BI/DW/ETL technologies such as Teradata Control Framework, Tableau, OBIEE, SAS, Apache Spark, Hive.

• Experience in data observability handling tools to monitor data quality and pipeline performance in real-time.

• Experience in AIML integrations like designing infrastructure for AI, including managing Vector Databases and embeddings in a plus.

• Good to have certified in any of the Cloud Data Engineering (ex: AWS certified Data Engineering etc.

Education Qualification: Bachelor’s degree or master’s degree in engineering in Computer Science/Information Technology