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Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and, Interactive, Technology, and Operations services, all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 738,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners, and communities. Visit us at www.accenture.com. 
This is the beginning of a new Data & AI decade that will reshape work and society has begun. Accenture is stepping boldly into this future with a clear strategy and purpose: to help clients optimize and reinvent their business with data & AI — backed by a $3B investment and commitment to our people to do industry-defining work.
With over 45,000 professionals dedicated to Data & AI, Accenture’s Data & AI organization brings together our Experienced Innovation, Strategic Investment, Exceptional Talent, and Power Ecosystem.
Role Summary
We are seeking a highly skilled Python Data Engineer with hands-on experience in designing, building, and scaling data platforms and products using modern cloud technologies. This role requires an individual with expertise in full-stack python development, cloud data platforms (e.g, AWS Redshift, GCP BigQuery, Microsoft Fabric, Snowflake, Databricks) and knowledge of modern data modeling and storage formats (e.g., Parquet, Iceberg, JSON, SQL, and others).
The ideal candidate will also have experience in AI and Generative AI frameworks and technologies, supporting the data requirements for advanced ML and Generative AI capabilities.
Responsibilities
Design, develop, and deploy high-performance Python-based data pipelines for structured, semi-structured, and unstructured data.
Implement data processing solutions with batch, real-time, and event-driven data processing frameworks.
Enforce data integrity, lineage, and observability by developing resilient and maintainable code.
Adopt and implement modern data architecture principles (e.g., data mesh, knowledge graphs, and ontologies).
Partner with data scientists, Generative AI engineers, and ML engineers to deploy AI-ready datasets.
Work in Agile/Scrum teams, contributing to code reviews, documentation, and DevOps processes.
Participate in agile development processes, using tools like Git and Jira to manage workflows and sprints.
Ensure the security and compliance of data products through the implementation of appropriate controls.