Role Description We're looking for a passionate Data Engineer II to help build and scale the data platform that powers analytics, product insights, and data-driven decision making across the organization. You'll work on modern data technologies including Kafka, Maxwell, Spark, S3, Trino, BigQuery, dbt, and Metabase to build reliable, scalable, and high-performance data systems. From real-time data ingestion and distributed data processing to dimensional modeling and data platform development, you'll play a key role in shaping the foundation of our data ecosystem. As part of the Data Engineering team, you'll: - Design and build robust data pipelines. - Implement modern data lake architectures. - Develop reusable data models. - Create trusted datasets that empower Product, Analytics, Data Science, and Business teams. - Contribute to improving our engineering standards by focusing on performance, reliability, observability, automation, and developer experience. This role is ideal for someone who enjoys solving complex data engineering challenges, building scalable platforms, and continuously improving how data is collected, transformed, and consumed across the organization. If you're excited about building modern data platforms, working with large-scale distributed systems, and having a meaningful impact on the company's data strategy, we'd love to hear from you. Qualifications - 4+ years of hands-on experience designing and building scalable data platforms, data lakes, and data warehouses. - Strong proficiency in Spark (Scala, python) and SQL, with experience building production-grade data pipelines and distributed data processing applications. - Hands-on experience with Apache Spark and a solid understanding of distributed data processing, performance tuning, and optimization. - Experience building batch and streaming data pipelines using technologies such as Kafka, CDC/Maxwell, or similar event-driven architectures. - Strong understanding of modern data lake architectures, including Medallion Architecture, data modeling, partitioning, and storage optimization. - Experience working with cloud-native data platforms and technologies such as Amazon S3, BigQuery, Trino, or similar analytics engines. - Solid experience designing dimensional models, star schemas, and building reliable data marts that support analytics and business intelligence. - Hands-on experience with dbt, including developing reusable models, implementing automated testing, and maintaining documentation. - Strong knowledge of data quality, observability, lineage, and engineering best practices to build reliable and maintainable data products. - Experience optimizing large-scale data pipelines, SQL queries, and distributed processing jobs for performance, scalability, and cost efficiency. - Familiarity with CI/CD, Git-based development workflows, infrastructure automation, and modern software engineering best practices. - Excellent problem-solving skills with the ability to independently own projects from design through production. - Strong communication and stakeholder management skills, with experience collaborating across Product, Engineering, Analytics, and Business teams. - A passion for building scalable data platforms and continuously improving developer experience, platform reliability, and operational excellence. Requirements - Design, build, and maintain scalable batch and real-time data pipelines using Maxwell, Kafka, Spark, and dbt to power analytics and business-critical applications. - Develop and optimize data models following Medallion Architecture (Bronze, Silver, Gold) to create reliable, reusable, and high-quality datasets. - Build and maintain cloud-native data platforms using S3, Spark, Trino, and BigQuery, ensuring scalability, reliability, and cost efficiency. - Design robust data ingestion frameworks leveraging CDC (Maxwell), Kafka, and event-driven architectures to support near real-time data processing. - Create, optimize, and maintain data warehouses and data marts that enable fast, reliable reporting and self-service analytics. - Partner closely with Product Managers, Data Analysts, Backend Engineers, and Business stakeholders to translate business requirements into scalable data solutions. - Develop reusable dbt models, testing frameworks, and documentation to improve data quality, governance, and developer productivity. - Optimize Spark jobs, Trino queries, and storage layouts for performance, reliability, and cost efficiency. - Own the end-to-end lifecycle of critical data pipelines, ensuring high availability, monitoring, SLA adherence, and proactive incident resolution. - Build and enhance the core data platform by developing reusable frameworks, automation, CI/CD pipelines, and engineering best practices. - Ensure data quality through validation, monitoring, lineage, and observability while implementing best practices for security and governance. - Enable analytics teams by delivering trusted datasets, semantic models, and dashboards that power decision-making through Metabase. Benefits - Inclusive and Diverse Environment: We foster an inclusive and diverse workplace that values innovation and offers remote environments. - Competitive Compensation: Our compensation packages are highly competitive and include potential share options for certain roles. - Personal Growth and Development: We are committed to your personal and professional growth, providing regular training and an annual learning stipend to help you advance your career in a dynamic environment. - Autonomy and Mentorship: You'll enjoy a high degree of autonomy in your role, supported by mentorship and ambitious goals that pave the way for both your success and the company's growth.

Role Description The DE&A - Core - Cloud Data Engineering role is a critical position within Zensar Technologies, responsible for driving cloud-based data engineering initiatives. The successful candidate will lead a team of data engineers, ensuring the efficient and effective delivery of projects. With a focus on Azure, they will also have experience with other cloud platforms, enabling them to provide diverse solutions to clients. Qualifications - Experience in cloud-based data engineering. - Proficiency in Azure and other cloud platforms. - Leadership experience in managing data engineering teams. Requirements - Strong understanding of data engineering principles. - Ability to deliver projects efficiently and effectively. - Experience with diverse cloud solutions. Benefits - Inclusive workplace culture. - Opportunities for personal and professional growth. - Commitment to employee well-being.

• Design, build, and maintain enterprise data architectures supporting Supply Chain execution and performance measurement • Develop data models, pipelines, and integration frameworks • Lead data migrations, conversions, and performance optimization efforts • Oversea testing, deployment, maintenance, and continuous improvement of data systems • Ensure adherence to data quality, security, and compliance standards

Title: Chapter Lead, Data Science (Operations) Location: Australia Full time Job requisition id REQ248859 Job Description: Permanent Full Time Opportunity Drive the future of AI innovation at scale You are a visionary leader with a growth mindset, combining deep technical fluency with the ability to inspire and scale impact across the enterprise. Were one of the largest and most advanced Data Science practices in the country Together we can build state-of-the-art Data Science models that power seamless experiences for millions of customers See yourself in our team At the heart of the Chief Operations Office (COO), we're reimagining how we serve customers in operations through the power of transformative AI solutions. As a Chapter Lead reporting to the Chapter Area Lead of Data Science in COO, you'll balance hands-on technical contribution with people leadership-guiding and growing a team of data scientists while working in cross-functional squads with engineers and other experts to design and deliver innovative, responsible AI solutions. You'll stay at the forefront of emerging technologies, fostering a culture of curiosity, inclusion, and continuous learning, and translating complex ideas into high-impact outcomes for customers and colleagues. If you're passionate about shaping the future of AI while helping others thrive, we'd love you to lead with us. Key Responsibilities Lead AI Innovation Drive the design, construction and deployment of a range of AI projects Accelerate adoption of advanced AI capabilities Expand Data & AI Impact Across the Bank Identify high‑value AI use cases and champion the integration of Data Science methods across processes Ensure models follow best-practice engineering, governance, and deployment standards Drive Continuous Improvement & Business Value through AI Partner closely with operations teams to understand challenges and apply transformative AI capabilities Drive redevelopment, optimisation and monitoring of AI models to support strategic business outcomes We're interested in hearing from people with the following skills: Technical & People Leadership Demonstrated capability in driving outcomes that are reusable and can be leveraged across the group Demonstrated intellectual curiosity with a passion for experimenting and exploring emerging technologies Demonstrated ability to lead and mentor teams while remaining hands-on, fostering a supportive and inclusive team culture that values learning, thoughtful decision-making, and sustainable delivery of real-world impact. Technical Expertise Data: Experience designing and delivering AI solutions using a range of structured and unstructured data, with particular strength in natural language data. Machine Learning: Strong grounding in classical machine learning and deep learning, with the ability to select appropriate techniques-from simpler models to more complex approaches-based on problem context, constraints, and impact. Generative AI: Hands-on experience designing, building, and deploying Generative AI solutions, including RAG and agentic systems, with a pragmatic understanding of their limitations, risks, and costs. Statistical Expertise: Experience defining fit-for-purpose evaluation metrics, guiding experimentation, and applying sound statistical judgement to technical decision-making across the AI lifecycle. Production AI & MLOps: Proven ability to take models from prototype to production, including version control, CI/CD practices, containerisation, deployment, monitoring, and ongoing iteration. Data Engineering & Architecture: Working knowledge of data pipelines and integration patterns, and experience collaborating on scalable, reliable data and AI architectures. Cloud Platforms: Experience designing or deploying AI solutions on cloud platforms such as AWS or Azure, with awareness of scalability, cost, and operational considerations. Technical Leadership & Delivery: Ability to lead and mentor teams while remaining hands-on, balancing curiosity and continuous learning with a strong focus on delivery, value creation, and real-world impact. Working with us At CommBank, we advocate and facilitate a culture of inclusion and respect, celebrating all cultures, abilities, genders, expressions of gender and sexual orientation Read more about our commitment to inclusion and diversity. Our people bring their diverse backgrounds and unique perspectives to build a respectful, inclusive, and flexible workplace. One where we're driven by our values, and supported to share ideas, initiatives, and energy. One where making a positive impact for customers, communities and each other is part of our every day. We're committed to being an accessible employer and want to make finding your dream job as easy as possible. If you experience any accessibility issues or if you require additional support, please contact HR Direct. We support our people with the flexibility to balance where work is done with a hybrid approach of at least half your time each month connecting in office. We also have many other flexible working options available including changing start and finish times, part-time arrangements and job share to name a few. Talk to us about how these arrangements might work for you. Here, you'll thrive. You'll be supported when faced with challenges and empowered to tackle new opportunities. We're hiring talent from across all of Australia and have opened technology hubs in Melbourne and Perth. We really love working here, and we think you will too. If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We're keen to support you with the next step in your career. We're aware of some accessibility issues on this site, particularly for screen reader users.