AWS Bigdata Architect

ARA Resources Pvt. Ltd.; Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

Hybrid work model PAN India

Global client exposure

Learning & growth opportunities

Job summary

ARA Resources Pvt. Ltd. is seeking a Senior AWS Bigdata Architect to lead Knowledge Graph, semantic layer, ontology, and AI knowledge solutions on AWS.

You will translate complex business problems into scalable AI graph solutions, guiding technical direction across large enterprise programs. Responsibilities include building graph ingestion pipelines using Neptune, S3, Glue, Lambda, EMR, Redshift, and SageMaker; mentoring engineers; and delivering end-to-end graph-powered data and AI offerings

Qualifications

• Bachelor's degree in Computer Science, IT, Engineering, or related field.
• Strong hands-on knowledge of Knowledge Graph technologies and data modeling.
• Proficiency in Python with ML/AI tooling and ETL pipelines.

Responsibilities

• Engineer AWS-based knowledge engineering solutions and graph pipelines on AWS services.
• Lead Knowledge Graph development and semantic modeling across large programs.
• Collaborate with stakeholders to deliver graph-powered data and AI offerings.

Job description

About ARA's Client – Global Professional Services and Technology Leader

ARA's Client is a leading global professional services company, helping the world’s businesses and governments build their digital core, optimize operations, and accelerate growth. They are a talent- and innovation-led organization with approximately 791,000 people serving clients in over 120 countries. ARA's Client leverages their strength in technology, cloud, data, and AI with unmatched industry experience to create tangible value at speed and scale.

Role Summary

ARA's Client is seeking a Senior AWS Bigdata Architect to lead significant workstreams in Knowledge Graph, semantic layer, ontology, and AI knowledge solutions on Amazon Web Services (AWS). This role involves translating complex business problems into scalable AI and Knowledge Graph solutions, guiding technical direction, and contributing to thought leadership within large enterprise programs.

Key Responsibilities

• Engineer AWS-based knowledge engineering solutions using services such as Amazon Neptune, S3, Glue, Lambda, EMR, Redshift, Athena, OpenSearch, Bedrock, and SageMaker.
• Build graph ingestion pipelines, semantic data products, vector integrations, LLM grounding layers, APIs, and governed access patterns on AWS.
• Lead the development of Knowledge Graph solutions that transform client data architecture within a large program scope.
• Direct the design, development, and implementation of AI, semantic layer, ontology, taxonomy, schema, and graph modeling solutions.
• Collaborate with project leaders, delivery leads, client stakeholders, architects, and AI/Data engineers to create impactful graph-powered data and AI offerings.
• Develop strong client relationships, establish trust as a key advisor, and effectively communicate the business value of semantic layer and knowledge graph solutions.
• Provide thought leadership on technology trends, innovation opportunities, limitations, risks, and practical adoption of Knowledge Graphs, semantic AI, and LLM grounding.
• Design, evaluate, and maintain ontologies, schemas, standards, and reusable engineering patterns while guiding teams on data model quality.
• Lead a team or workstream within larger programs, mentoring engineers and reviewing design, code, and configurations.
• Drive end-to-end delivery for assigned scope and demonstrate value to business and technology stakeholders through collaborative efforts.

Must-Have Qualifications

• Minimum 12-16 years of overall experience, with a Bachelor's degree in Computer Science, IT, Engineering, or a related field.
• Minimum 3 years of hands-on experience with Knowledge Graph technologies such as RDF, SPARQL, LPG, SHACL, OWL, graph query languages, and schema design.
• Minimum 3 years of experience in schema design, ontology management, semantic modeling, taxonomy management, metadata management, and knowledge graph curation.
• Minimum 3 years designing and developing Knowledge Graph solutions and graph-based ML models across functional and technical workstreams.
• Minimum 2 years implementing end-to-end data pipelines for AI applications, especially LLM-enabled or enterprise knowledge applications.
• Minimum 4 years of experience with relational databases, object stores, graph databases (Stardog, Neo4j, Amazon Neptune), and vector databases.
• Hands-on experience building AWS-based knowledge engineering solutions with Amazon Neptune, S3, Glue, Lambda, EMR, Redshift, Athena, OpenSearch, Bedrock, and SageMaker.
• Strong Python experience with frameworks and tools such as TensorFlow, PyTorch, PySpark, SQL, SPARQL, SHACL, Apache Airflow, and ETL/ELT pipeline tooling.

Nice to Have

• 2+ years of hands-on experience with multi-cloud platforms, specifically AWS specialization with exposure to Azure or GCP.
• AWS certifications such as Solutions Architect, Data Engineer, or Machine Learning/AI Specialty.
• Industry experience in BFSI, healthcare, retail, telecom, manufacturing, energy, public sector, or life sciences, including domain ontologies and compliance needs.
• External client-facing consulting experience, proposal support, solution shaping, or pre-sales exposure.
• Strong technical leadership and mentorship capabilities for complex engineering teams.
• Excellent cross-functional collaboration and stakeholder communication skills.
• Demonstrated ownership mindset with a focus on delivering high-quality, impactful solutions.
• Ability to translate intricate technical concepts and solutions into clear business value.
• Proactive thought leadership and a commitment to continuous learning in emerging technologies.
• Exceptional problem-solving acumen and strategic thinking for enterprise-level challenges.

Why Join Us

• Lead and shape cutting-edge AI and Knowledge Graph initiatives on AWS for diverse global clients.
• Contribute to thought leadership and influence the future direction of knowledge engineering practices.
• Collaborate with a global team of experts in a talent- and innovation-led environment.
• Drive significant business impact by transforming client data architectures and enabling advanced AI capabilities.
• Access unparalleled opportunities for continuous learning, mentorship, and professional growth in advanced cloud and AI technologies.
• Work in a flexible hybrid model that balances team collaboration with individual autonomy across PAN India.