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Technology and Transformation - Engineering - Consultant - Data Engineer Knowledge graph - Bengaluru

Deloitte -
Bengaluru, Karnataka

Apply Now

Job details

9 days ago

Qualifications

Ontology
CI/CD
Microsoft Access
Azure
Business intelligence
Computer Science
Big data
Spark
Git
SPARQL
SQL
RBAC
Bachelor's degree
Machine learning
Neo4j
Continuous integration
REST
RDF
APIs
B.E.
S3
JSON
GraphQL
Metadata
Graph databases
Python
Information Technology

Full job description

Job requisition ID :: 103724

Date: Jun 4, 2026

Location: Bengaluru

Designation: Consultant

Entity: Deloitte Touche Tohmatsu India LLP

Technology and Transformation - Engineering - Consultant - Data Engineer Knowledge graph - Bengaluru

Job requisition ID : 103724
Location: Bengaluru
Entity: Deloitte Touche Tohmatsu India LLP

The Team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.

Your work profile

Deloitte is looking for a Data Engineer with strong expertise in Knowledge Graphs, with GraphDB (RDF/OWL/SPARQL) as the preferred primary skillset, and Neo4j/Cypher as an alternative.
You will design and operate graph‑centric data architectures and integrate them with Snowflake to deliver high‑quality, governed, and semantically rich data products across the organization.

Key Skills & Competencies

Knowledge Graph Engineering (Primary Focus)
Design, build, and maintain RDF/OWL‑based knowledge graphs using GraphDB or similar triple stores.
Develop ontologies, vocabulary, and semantic schemas to accurately represent business domains.
Write and optimize SPARQL queries and implement reasoning/inference rules as needed.
Manage ingestion pipelines to populate and update RDF graphs, ensuring consistency and performance.
Support property graph modeling as secondary expertise using Neo4j/Cypher where applicable.
Build and maintain curated Snowflake data products: domain‑aligned tables, views, and semantic layers.
Implement ELT with Snowpipe, Streams, and Tasks, plus performance optimization and governance controls.
Ensure strong documentation, data quality, lineage, and versioning for all Snowflake datasets.
Develop and manage EL/ETL/ELT pipelines that feed both the knowledge graph and Snowflake.
Use orchestration tools such as Airflow, Prefect, or Azure Data Factory for automation.
Implement CI/CD for data workflows, with monitoring, alerting, and high‑reliability operational practices.
Apply RBAC, masking, and row/column‑level security in both Snowflake and graph systems.
Maintain lineage, metadata, and standardized documentation across all data assets.
Define schema standards, semantic conventions, and data contracts with producers and consumers.
Partner with domain experts, analysts, engineers, and ML teams to understand semantics and translate concepts into graph structures and data products.
Advocate for graph‑driven design and semantic consistency across domains.
Experience designing ontologies or complex semantic data models.
Familiarity with dbt or other ELT frameworks.
Exposure to Spark/Databricks.
Experience with lineage/metadata tools (OpenLineage, Purview, Collibra).
Experience building REST or GraphQL APIs for data access.

Preferred Qualifications

Education - B. tech / BE in Computer Science or Information Technology.

Success Metrics

4–6 years of hands‑on data engineering experience.
Strong, practical experience with GraphDB or any RDF/OWL/SPARQL‑based knowledge graph stack.
Experience with Neo4j/Cypher as secondary graph expertise.
Strong Snowflake ELT skills, including Snowpipe/Streams/Tasks and warehouse optimization.
Proficiency in SQL and Python.
Experience with structured and semi‑structured data (JSON, Parquet, Avro).
Cloud object storage (S3/ADLS/GCS) experience.
Hands‑on experience with Airflow/Prefect/ADF and Git‑based workflows.

Location and way of working:

Base location: Bengaluru
This profile involves travelling to client locations

Apply Now

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