S&C Global Network - AI - Song - Marketing Platform-Associate Manager

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.