Staff Data Engineer

Job Summary

Job Title: Staff Data Engineer

Location: Bangalore

Business & Team: Business Banking - EBB

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

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