Data Engineer - Industrial Data & AI Platforms

Accenture Industry X, part of Accenture, helps businesses thrive in the digital era by combining data and digital capabilities. Join us to experience how we deliver 360 value and collaborate with exceptional people,   cutting-edge   technology, and leading companies across various industries, making a significant impact worldwide.

Overview: We are looking for a Data Engineer with experience in industrial data environments such as digitalization initiatives, digital twins, and predictive maintenance. In this role, you will design and build scalable data pipelines and platforms that enable advanced analytics, machine learning, and AI use cases. You will work with heterogeneous industrial data sources, including technical documentation, legacy asset management systems, and industrial time-series data. The position requires strong collaboration with data scientists, domain experts, and engineering teams to transform complex operational data into structured, governed, and accessible datasets that support analytics, predictive maintenance, and AI-driven insights. Key Focus: Data Engineering & Platform Development: 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 Cloud Data Infrastructure: Implement and manage data solutions on AWS and/or 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 Data Governance & Data Management: Implement data governance practices, including metadata management, data quality, and lineage tracking Support the implementation and maintenance of data catalogs and metadata management tools Experience with Collibra or similar data governance platforms is a strong plus Analytics Enablement: Prepare curated datasets that support 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 Data Visualization & Insights: Support the creation of data-driven dashboards and insights using PowerBI Ensure data is structured and optimized for analytics and reporting consumption What you need to succeed:   Technical Skills: Experience in data engineering and data platform development Strong Python programming skills Experience building ETL/ELT pipelines Knowledge of AWS and/or Google Cloud Platform (GCP) Experience working with structured, semi-structured, and time-series data Familiarity with data modeling and data warehousing concepts Data Governance & Data Management: Understanding of data governance, metadata management, and data quality practices Experience with data catalog solutions Collibra knowledge is a plus Analytics & Visualization: Experience preparing datasets for analytics and machine learning use cases Knowledge of PowerBI for data presentation and dashboarding Nice to Have: Experience working with industrial data environments (manufacturing, asset management, IoT, predictive maintenance) Familiarity with digital twin or industrial AI use cases Exposure to machine learning or generative AI workflows Key Competencies: 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 Comfortable collaborating with data scientists, engineers, and domain experts Your life at Accenture   At Accenture,   we prioritize your health and