Job Overview

CGI is hiring a Senior Data Engineer for a full-time role in Hyderabad, Andhra Pradesh. The position focuses on data and knowledge engineering, with an emphasis on linked data, semantic models, enterprise ontologies, knowledge graphs, APIs, and modern data integration.

This opportunity is suited to experienced professionals who can work across software engineering and data engineering responsibilities. You will build and maintain linked data pipelines, transform information from relational and structured sources into semantic models, expose data through APIs, and contribute to data quality and governance practices.

The role also involves data mesh concepts, Azure cloud services, CI/CD, Agile delivery, and enterprise integration. Experience in enterprise environments, particularly financial services, is preferred.

Key Responsibilities

• Develop and maintain linked data pipelines using RDF and related semantic technologies.
• Design mappings that transform relational data and structured formats such as XML and JSON into semantic models.
• Integrate data products while following data mesh principles and enterprise data practices.
• Work with enterprise ontologies, vocabularies, metadata, and semantic models.
• Build APIs that expose semantic data and metadata for consuming applications and teams.
• Implement data quality validation rules using SHACL.
• Support API and system integration activities across enterprise data environments.
• Contribute to CI/CD pipelines and development workflows using Azure DevOps.
• Document data models, semantic structures, mappings, and data pipelines.
• Collaborate with Tech Leads and Product Owners to understand requirements and deliver reliable data solutions.
• Participate in Agile and Scrum practices.
• Improve the quality, reliability, and maintainability of data workflows.

Required Skills

Strong experience in data, software, or knowledge engineering is important for this position. Candidates should be comfortable programming in Python, Java, or a similar language and should understand APIs and enterprise system integration.

A strong foundation in semantic technologies is required. Applicants should understand RDF, RDFS, OWL, and SPARQL and have practical knowledge of data modelling, metadata, knowledge graphs, and ontologies.

The role also requires familiarity with structured formats such as JSON, XML, and CSV. Candidates should be able to use these formats when designing mappings and integrating source information into semantic models.

Basic DevOps knowledge is expected, including Git and CI/CD concepts. Exposure to Azure cloud services and experience working in Agile or Scrum teams are also relevant.

Preferred Skills

Experience with graph database platforms such as GraphDB, Stardog, or Neo4j is a plus. Knowledge of RML or YARRRML can be useful for source-to-semantic data mappings.

Candidates with experience in SHACL validation, Kafka, or Azure Event Hubs may have an advantage. Familiarity with data mesh concepts, GraphQL, or semantic APIs is also desirable.

Enterprise experience, particularly in financial services, is preferred because the role involves complex data environments and integration requirements.

Education

A Bachelor's degree in Computer Science or a related field, or a higher qualification, is required according to the job description.

Experience

The position details specify 8+ years of experience in data, software, or knowledge engineering. The qualifications section additionally states a minimum of 10 years of experience for candidates with a Bachelor's degree or higher.

Because the supplied posting contains two experience references, applicants should review the employer's official requirements carefully and ensure their profile meets the applicable criteria.

Required Technologies

• Python
• Java
• RDF
• RDFS
• OWL
• SPARQL
• JSON
• XML
• CSV
• Knowledge Graphs
• Ontologies
• Data Modelling
• Metadata
• Azure Cloud
• Git
• CI/CD
• Azure DevOps
• GraphDB
• Stardog
• Neo4j
• RML
• YARRRML
• SHACL
• Kafka
• Azure Event Hubs
• Data Mesh
• GraphQL
• Semantic APIs

Soft Skills

Clear communication is important because the role involves working with Tech Leads, Product Owners, and other stakeholders. Candidates should be able to explain data models, integration approaches, semantic structures, and technical decisions clearly.

Analytical thinking is valuable when handling complex enterprise data and resolving integration or data quality challenges. Strong documentation skills are also important because the position includes maintaining information about data models and pipelines.

The ability to work effectively within Agile and Scrum teams, contribute to technical decisions, manage priorities, and collaborate across functions will support success in this role.

Benefits of Working in this Role

This position provides exposure to advanced data engineering and knowledge engineering practices, including semantic data, knowledge graphs, ontologies, linked data, data mesh concepts, cloud platforms, APIs, and DevOps workflows. It can help experienced engineers deepen their expertise in enterprise data architecture and semantic technologies.

The supplied job description does not specify company-specific salary, bonuses, insurance, leave, or other employee benefits. Candidates should verify those details directly with CGI.

Work Mode

The job description identifies the employment type as full time but does not explicitly specify a remote, hybrid, or work-from-office arrangement.

Location

The main location is Hyderabad, Andhra Pradesh, India.

Who Should Apply

This opportunity is suitable for experienced Data Engineers, Knowledge Engineers, Semantic Data Engineers, Data Integration Engineers, and software professionals with strong data modelling and enterprise integration experience.

Candidates should be particularly interested if they have practical knowledge of RDF, RDFS, OWL, SPARQL, knowledge graphs, ontologies, APIs, and structured data formats. Professionals with Python or Java development experience and exposure to Azure, Git, CI/CD, and Agile delivery should also consider applying.

Freshers are not the target audience because the position requires substantial professional experience.

Career Growth

Experience in this role can support progression toward Senior Data Engineer, Lead Data Engineer, Knowledge Graph Engineer, Semantic Data Architect, Data Architect, Data Platform Engineer, or Enterprise Data Architecture roles. Building deeper expertise across semantic technologies, cloud platforms, APIs, data governance, and data mesh can broaden opportunities in modern enterprise data engineering.

Application Advice

Customize your resume to emphasize data engineering, software engineering, and knowledge engineering experience. Clearly state your professional experience and highlight projects involving linked data, semantic models, knowledge graphs, ontologies, or enterprise data integration.

Mention practical experience with RDF, RDFS, OWL, SPARQL, SHACL, JSON, XML, and CSV where applicable. If you have used GraphDB, Stardog, Neo4j, RML, YARRRML, Kafka, Event Hubs, GraphQL, or semantic APIs, include those technologies with relevant project context.

Also highlight Azure cloud exposure, Git, CI/CD, Azure DevOps, and Agile or Scrum experience. If you have worked in financial services or another complex enterprise environment, explain the nature of the systems and data problems you handled.

Before applying, carefully compare your experience against the employer's stated requirements, particularly the experience criteria and semantic technology expectations.