Accenture Applied Intelligence practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition As part of our Analytics practice, you will join a worldwide network of over 20,000 smart and driven colleagues experienced in leading statistical tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance. Analyst/Consultant in Applied Intelligence A Data Engineering Analyst or Consultant professional ensures the reliability, scalability, and efficiency of data pipelines and platforms, enabling teams to deliver actionable insights and AI/ML solutions. This role combines hands-on development, automation, and monitoring, translating business and data requirements into robust, production-ready data architectures while mentoring team members and enforcing best practices. Duties And Responsibilities Work across all phases of data projects: Define infrastructure, data requirements, and operational standards aligned with business goals in the marketing practice Build, maintain, and optimize ETL/ELT pipelines, batch and streaming workflows, and data transformation processes. Implement CI/CD for data pipelines, automate deployments, and ensure operational reliability and observability. Collaborate with data science, analytics, and product teams to provision data for ML/AI workloads, including feature stores and vector databases. Monitor and troubleshoot pipeline performance, storage, compute costs, and SLAs. Partner with managers and leadership to convert infrastructure and operational insights into actionable recommendations. Lead small project pods, mentor team members, review code, enforce standards, and drive process improvements. Contribute to internal frameworks, runbooks, templates, and knowledge assets. Ensure data security, compliance, and governance practices are followed across pipelines and deployments.