Data Engineer at Accenture
Sydney, New South Wales, Australia -
Full Time


Start Date

Immediate

Expiry Date

21 Nov, 25

Salary

0.0

Posted On

21 Aug, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

ABOUT ACCENTURE

We work with one shared purpose: to deliver on the promise of technology and human ingenuity. Every day, more than 791,000 of us help our stakeholders continuously reinvent. Together, we drive positive change and deliver value to our clients, partners, shareholders, communities, and each other.We believe that delivering value requires innovation, and innovation thrives in an inclusive and diverse environment. We actively foster a workplace free from bias, where everyone feels a sense of belonging and is respected and empowered to do their best work.At Accenture, we see well-being holistically, supporting our people’s physical, mental, and financial health. We also provide opportunities to keep skills relevant through certifications, learning, and diverse work experiences. We’re proud to be consistently recognized as one of the World’s Best Workplaces™.Join Accenture to work at the heart of change. Visit us at www.accenture.com
Join Accenture’s Modern Data Platform and Applied Intelligence practice, where you’ll be instrumental in building robust, scalable data solutions that empower clients to make informed decisions. You’ll participate in every stage—from delivery planning and data architecture to pipeline design, production implementation, and ongoing optimization—across cloud, hybrid, and on-premise environments.

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Responsibilities
  • Design, develop, and maintain data pipelines, ETL/ELT workflows, and data architectures that support reporting, dashboards, and analytics use cases.
  • Collaborate with stakeholders—data architects, analysts, and business users—to translate complex requirements into scalable, production-grade data solutions.
  • Deliver end-to-end data engineering—from planning and analysis through to deployment and production—and support batch, streaming, and event-driven workflows.
  • Apply best practices in data modeling, governance, data quality, and observability to ensure robustness and maintainability of data platforms.
  • Work under Agile or hybrid SDLC methodologies to deliver high-value client outcomes and ensure seamless collaboration with delivery teams.
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