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Accenture

Advises businesses and runs their technology

Data Engineer - Industrial Data & AI Platforms

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedHybrid

About the Job

Requirements

  • Experience in data engineering and data platform development.
  • Strong Python programming skills.
  • Experience building extract, transform, and load (ETL) or extract, load, and transform (ELT) pipelines.
  • Knowledge of AWS and/or Google Cloud Platform.
  • Experience working with structured, semi-structured, and time-series data.
  • Familiarity with data modeling and data warehousing concepts.
  • Understanding of data governance, metadata management, and data quality practices.
  • Experience with data catalog solutions.
  • Experience preparing datasets for analytics and machine learning use cases.
  • Knowledge of Power BI for data presentation and dashboarding.
  • Strong analytical thinking and problem-solving skills.
  • Ability to work with complex, heterogeneous, and legacy data sources.
  • Capability to bridge data engineering with analytics and AI use cases.
  • Ability to collaborate with data scientists, engineers, and domain experts.

Responsibilities

  • Design, develop, and maintain scalable ETL/ELT pipelines for ingesting and transforming industrial and operational data.
  • Build data pipelines using Python and modern data engineering frameworks.
  • Integrate heterogeneous data sources, including legacy asset management systems, IoT data, industrial time-series data, and technical documentation.
  • Support the development of data platforms enabling analytics, machine learning, and AI use cases.
  • Implement and manage data solutions on AWS, Google Cloud Platform, and/or Azure.
  • Design data architectures supporting large-scale analytics and industrial AI applications.
  • Work with cloud-native services for data ingestion, processing, storage, and orchestration.
  • Implement data governance practices, including metadata management, data quality, and lineage tracking.
  • Support the implementation and maintenance of data catalogs and metadata management tools.
  • Prepare curated datasets supporting predictive maintenance, digital twin, and engineering analytics use cases.
  • Enable data scientists and AI teams to build machine learning and AI solutions on well-structured data.
  • Create data models and reporting datasets for business users.
  • Support the creation of data-driven dashboards and insights using Power BI.
  • Ensure data is structured and optimized for analytics and reporting consumption.

Desired Qualifications

  • Experience with Collibra or similar data governance platforms.
  • Experience working with industrial data environments such as manufacturing, asset management, IoT, or predictive maintenance.
  • Familiarity with digital twin or industrial AI use cases.
  • Exposure to machine learning or generative AI workflows.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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