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Accenture

Advises businesses and runs their technology

Knowledge Engineer

Data ManagementConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree or equivalent is required.
  • At least 15 years of experience in Microsoft Azure Data Services is required.
  • At least 6 years of experience with knowledge graph technologies, including RDF, SPARQL, LPG, and SHACL, is required.
  • At least 6 years of experience in schema design, ontology management, and knowledge graph curation is required.
  • At least 4 years of experience designing and developing knowledge graph solutions and graph-based machine learning models, both functional and technical, is required.
  • At least 3 years of experience implementing end-to-end data pipelines for artificial intelligence applications, especially large language models, including hands-on design and configuration, is required.
  • At least 6 years of experience with relational databases, object stores, graph databases such as Stardog, Neo4j, and Amazon Neptune, and vector databases is required.
  • At least 6 years of managerial experience leading people is required, along with the ability to explain the value of semantic layers and knowledge graphs to senior business and technology stakeholders, a track record in sales or pre-sales, delivery of data transformation programs, and team development.
  • Practical experience with natural language processing or search techniques and prompt engineering is required.
  • Experience with large language models for enterprise-scale applications is required.
  • At least 5 years of hands-on experience with cloud platforms such as AWS, Azure, or GCP is required.
  • At least 5 years of experience with Python, frameworks such as TensorFlow and PyTorch, and tools for building ETL pipelines such as Apache NiFi or Airflow is required.
  • External client-facing consulting experience is required.
  • A Ph.D. in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field is required.
  • Broad experience in diverse machine learning techniques and agentic systems is required.
  • Strong collaboration skills and the ability to work across engineering, research, and product teams across multiple time zones are required.
  • Proficiency in Microsoft Azure Data Services is required.
  • Expertise in designing and implementing knowledge graphs and semantic models is required.
  • Experience capturing and structuring unstructured data into ontologies is required.
  • The ability to apply advanced analytics techniques to extract insights from complex knowledge representations is required.
  • Familiarity with cloud-based data services and scalable data architecture is required.
  • Fifteen years of full-time education is required.

Responsibilities

  • Design and structure knowledge frameworks that enable artificial intelligence systems to reason and make informed decisions.
  • Capture and translate expert and unstructured knowledge into ontologies, knowledge graphs, and semantic models, ensuring accuracy and context for automation and insights.
  • Apply advanced analytics to knowledge graphs to drive problem-solving and actionable insights.
  • Lead the complete knowledge engineering scope on strategic and complex programs, including thought leadership, innovation, and assets for the discipline.
  • Set strategy and architecture for complex programs that formulate real-world problems into scalable artificial intelligence and knowledge graph solutions.
  • Lead and develop teams of engineers, building capability across the discipline and guiding adoption of new methods and algorithms.
  • Define standards for designing, evaluating, and maintaining ontologies across programs.
  • Shape methodologies and data architectures, and make the case for their value at scale to senior stakeholders.
  • Lead the creation of thought leadership, innovation, and reusable assets that advance the discipline.
  • Partner with business and technical leaders to direct end-to-end delivery across complex, multi-stakeholder programs.
  • Lead the knowledge graph solution scope for strategic and complex clients, transforming data architecture.
  • Own the design, development, and implementation of artificial intelligence and semantic solutions across the program.
  • Partner with project leaders, delivery leads, and senior client stakeholders to create graph-powered offerings.
  • Develop trusted-advisor relationships with senior client stakeholders.
  • Make and defend the business case for semantic-layer solutions at the executive level.
  • Lead sales and pre-sales efforts and shape data transformation programs.
  • Drive practice thought leadership, innovation, and asset development on trends and agentic technologies, and develop the teams who deliver them.
  • Collaborate with stakeholders to align knowledge frameworks with organizational goals and evolving technology.
  • Mentor and guide junior team members to foster skill development and knowledge sharing.
  • Provide expertise and advisory guidance, make team decisions, engage with multiple teams on key decisions, and provide solutions to problems that apply across multiple teams.

Desired Qualifications

  • Experience with machine learning is desirable.

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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