Data Engineer - Industrial Data & AI Platforms

About the role

Accenture Industry X is seeking a Data Engineer to design and build scalable data pipelines and platforms for industrial data, supporting advanced analytics, machine learning and AI use cases across digital twins, predictive maintenance and other digitalisation initiatives.

Key responsibilities

• Design, develop and maintain ETL/ELT pipelines using Python and modern data‑engineering frameworks.
• Integrate heterogeneous industrial sources such as legacy asset‑management systems, IoT streams, time‑series data and technical documentation.
• Implement cloud‑native data solutions on AWS, Google Cloud Platform or Azure, leveraging ingestion, processing, storage and orchestration services.
• Apply data‑governance practices, including metadata management, data quality checks and lineage tracking, and support catalog tools like Collibra.
• Prepare curated datasets for predictive‑maintenance, digital‑twin and engineering analytics, and enable data scientists to build AI models.
• Support creation of PowerBI dashboards and ensure data is optimised for reporting.

Required profile

• Strong experience in data engineering and platform development, with solid Python programming skills.
• Hands‑on experience building ETL/ELT pipelines and working with structured, semi‑structured and time‑series data.
• Proficiency with cloud platforms (AWS, GCP or Azure) and familiarity with data‑modeling and warehousing concepts.
• Understanding of data‑governance, metadata management and data‑quality practices; Collibra experience is a plus.
• Ability to collaborate with data scientists, engineers and domain experts in complex, heterogeneous data environments.

Required skills

• Python
• AWS, Google Cloud Platform, Azure
• ETL/ELT pipeline development
• Data modeling & data warehousing
• Time‑series data handling
• Collibra (or similar data‑governance tools)
• PowerBI