Staff Data Engineer

Posted 7 Days Ago
Be an Early Applicant
2 Locations
In-Office
Senior level
Fintech • Financial Services
The Role
Design and deliver scalable batch, streaming and analytical data pipelines and reusable semantic data products. Automate data product lifecycles, implement data matching, cleansing, quality and observability controls, support ML productionisation, build CI/CD with GitHub Actions, and provide technical leadership and governance for secure, resilient data solutions.
Summary Generated by Built In

Staff Data Engineer

Role Purpose

The Staff Data Engineer is a senior technical contributor responsible for designing and delivering scalable, reliable and secure data solutions. The role provides technical leadership across data engineering, analytical pipelines, data ontology, data matching, data cleansing, MLOps and automation.

A key focus is transforming complex source data into trusted, reusable and dashboard-ready data products, while automating their development, deployment, testing and ongoing management.

Key Responsibilities:

  • Design and build scalable batch, streaming and analytical data pipelines.

  • Transform source data into trusted, reusable and analysis-ready datasets.

  • Create curated data layers, semantic models and reusable data products for dashboards, reporting and analytics.

  • Automate the dashboard data lifecycle, including ingestion, transformation, testing, deployment, monitoring, refresh and issue remediation.

  • Design and implement agentic workflows that coordinate data preparation, quality validation, metadata generation, dashboard updates and operational support.

  • Build and maintain CI/CD pipelines using GitHub Actions.

  • Design data models, ontologies, taxonomies and common data definitions.

  • Implement data matching, entity resolution, deduplication and data cleansing solutions.

  • Build automated data quality, validation, reconciliation and observability controls.

  • Develop solutions for large and complex datasets using big data and distributed processing technologies.

  • Support the productionisation and monitoring of machine learning and open-weight models.

  • Develop production-grade solutions using Python and/or R.

  • Establish engineering standards, mentor engineers and provide technical guidance.

  • Ensure data solutions meet security, privacy, resilience and governance requirements.

Essential Experience:

  • Strong experience in data engineering and large-scale data platforms.

  • Strong algorithmic optimisation capabilities

  • Advanced Python and/or R programming skills, with strong SQL capability.

  • Experience building production-grade analytical, batch or streaming pipelines.

  • Experience preparing reusable datasets and semantic data layers for dashboards, reporting and analytics.

  • Strong experience implementing CI/CD pipelines using GitHub Actions.

  • Experience automating data and analytical product lifecycles, including testing, deployment, monitoring and release management.

  • Experience designing or implementing agentic workflows, AI-driven automation or intelligent orchestration.

  • Experience with big data and distributed processing technologies.

  • Experience with data modelling, semantic modelling or data ontology.

  • Experience with data matching, entity resolution, deduplication and data cleansing.

  • Experience implementing data quality and data observability controls.

  • Exposure to MLOps and the productionisation of analytical or machine learning models.

  • Strong cloud platform, software engineering, automated testing and infrastructure-as-code experience.

  • Demonstrated technical leadership and mentoring capability.

Desirable Experience:

  • Experience evaluating, fine-tuning, deploying or operating open-weight models.

  • Exposure to retrieval-augmented generation, embeddings, vector databases or model-serving technologies.

  • Experience applying AI agents to data engineering, analytics or dashboard operations.

  • Exposure to cyber security controls and secure data engineering.

  • Exposure to identity and access management, identity governance or identity-related datasets.

  • Experience in regulated or risk-sensitive environments.

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.

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Skills Required

  • Strong experience in data engineering and large-scale data platforms.
  • Strong algorithmic optimisation capabilities.
  • Advanced Python and/or R programming skills.
  • Strong SQL capability.
  • Experience building production-grade analytical, batch or streaming pipelines.
  • Experience preparing reusable datasets and semantic data layers for dashboards and analytics.
  • Strong experience implementing CI/CD pipelines using GitHub Actions.
  • Experience automating data and analytical product lifecycles including testing, deployment, monitoring and release management.
  • Experience designing or implementing agentic workflows, AI-driven automation or intelligent orchestration.
  • Experience with big data and distributed processing technologies.
  • Experience with data modelling, semantic modelling or data ontology.
  • Experience with data matching, entity resolution, deduplication and data cleansing.
  • Experience implementing data quality and data observability controls.
  • Exposure to MLOps and the productionisation of analytical or machine learning models.
  • Strong cloud platform, software engineering, automated testing and infrastructure-as-code experience.
  • Demonstrated technical leadership and mentoring capability.

Commonwealth Bank Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Commonwealth Bank and has not been reviewed or approved by Commonwealth Bank.

  • Leave & Time Off Breadth The bank offers additional Life Leave, the option to purchase up to four extra weeks, pet leave, and paid volunteering leave alongside flexible-working options. Public materials indicate these leave features compare well within Australian banking.
  • Parental & Family Support Permanent employees can access up to 18 weeks of paid parental leave, and superannuation is paid for up to 34 weeks of unpaid parental leave. These provisions extend support for new parents beyond standard settings.
  • Wellbeing & Lifestyle Benefits Access includes CBHS Health Fund, Fitness Passport, a 24/7 wellbeing platform with telehealth, an Employee Assistance Program, and employer‑paid income protection for up to two years, alongside staff banking perks and share plans. This combination provides day‑to‑day value across health, protection, and financial perks.

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The Company
HQ: Sydney, New South Wales
52,000 Employees
Year Founded: 1911

What We Do

Australia’s leading provider of financial services including retail, premium, business and institutional banking, funds management, superannuation, insurance, investment and sharebroking products and services. We are a business with more than 800,000 shareholders and over 52,000 employees. We offer a full range of financial services to help all Australians build and manage their finances.

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