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Accenture

Advises businesses and runs their technology

Agentic AI Data Migration Lead

Data EngineeringConfirmed live in the last 24 hours
Full-timeParis, FranceNo salary listed

About the Job

Requirements

  • At least 12 years of relevant professional experience in IT, with substantial experience in Data and AI, Data Engineering, Data Architecture, Data Migration, or Cloud Data Transformation.
  • Experience leading medium- to large-scale data migration and modernization programs.
  • Significant experience designing or implementing solutions using generative AI and/or agentic AI, ideally for Data Engineering, Data Migration, or Cloud Transformation.
  • Strong command of migration strategies and approaches, including Rehost, Replatform, Refactor, Repoint, and Modernize.
  • Solid knowledge of modern data architectures, cloud platforms, and integration and migration patterns.
  • Proficiency in at least two to three cloud or data technologies among Azure, AWS, Google Cloud, Snowflake, Databricks, and Microsoft Fabric.
  • Strong understanding of Data Engineering, ETL/ELT, data integration, orchestration, data modelling, distributed processing, and migration patterns.
  • Experience with legacy data technologies such as Informatica, Talend, Ab Initio, Teradata, or equivalent technologies.
  • Experience designing and implementing solutions involving databases, data warehouses, data lakes, ETL platforms, reporting, and other legacy data environments.
  • Understanding of agentic AI concepts, including autonomous agents, agent orchestration, tool calling, workflow automation, human-in-the-loop, and AI governance.
  • Ability to identify and prioritize agentic AI use cases with concrete business and technical value.
  • Experience estimating, planning, governing delivery, and managing risk in complex programs.
  • Knowledge of data quality, governance, security, lineage, reconciliation, and testing.
  • Ability to lead technical teams and collaborate with Business, Architecture, Engineering, Cloud, AI, and Delivery teams.
  • Experience in cross-functional, multicultural, and international environments.

Responsibilities

  • Lead the strategy, architecture, and roadmap for data migration and modernization programs incorporating generative AI and agentic AI capabilities.
  • Analyze legacy data environments and define migration or modernization strategies suited to business, technical, and data needs.
  • Design AI-native and agentic approaches to automate and accelerate migration phases.
  • Define migration approaches, including Rehost, Replatform, Refactor, Repoint, and Modernize, and identify opportunities for AI automation.
  • Design end-to-end migration architectures covering ingestion, integration, transformation, storage, orchestration, data quality, testing, and reconciliation.
  • Define migration approaches for data components including databases, data warehouses, data lakes, storage objects, ETL/ELT jobs, pipelines, orchestration, reports, and data models.
  • Design and implement AI agents and agentic workflows to automate legacy-code analysis, data mapping, code generation and transformation, documentation, testing, and remediation.
  • Identify use cases for autonomous or semi-autonomous agents and ensure appropriate controls, human validation, and governance.
  • Evaluate and recommend suitable technologies, including Azure, AWS, Google Cloud, Databricks, Snowflake, BigQuery, Microsoft Fabric, Informatica, Talend, Ab Initio, Power BI, and generative AI and agentic AI technologies.
  • Define patterns, frameworks, and reference architectures to industrialize AI-augmented data migrations.
  • Lead technical assessments, evaluate complexity, and identify risks, dependencies, and automation opportunities.
  • Define approaches for data quality, governance, security, lineage, reconciliation, testing, and human-in-the-loop controls.
  • Provide technical leadership to Data Engineering, Cloud, AI, and Migration teams and develop their skills in agentic AI technologies.
  • Collaborate with global delivery teams to ensure effective execution and industrialization of solutions.
  • Engage with senior client stakeholders to present strategy, architecture, agentic AI use cases, risks, and technology decisions.
  • Contribute to commercial proposals, solutioning, estimates, statements of work, and client presentations.
  • Prepare solution, architecture, and demonstration materials for leadership and clients.
  • Support the transition from strategy, assessment, and solutioning to implementation and delivery.
  • Monitor developments in Data, Cloud, generative AI, and agentic AI technologies and identify new opportunities to automate and industrialize migrations.
  • Lead and develop the Data Migration practice for France and BeLux.

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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