Role Summary
Build the connectivity, profiling, and graph/search backbone that the ontology runs on — turning raw source systems into clean, lineage-tracked, query able knowledge.
Key Responsibilities
• Own data source connectivity: build and maintain adapters to connect master data and work-ticket APIs via BigQuery, Cloud SQL, REST/Apigee, GCS, and Pub/Sub.
• Own data profiling and inference: profile source data for quality, statistical patterns, dependencies, and lineage ahead of ontology mapping.
• Stand up and operate the Knowledge Core — the graph and search backbone — using Spanner Graph (or an equivalent property-graph/RDF platform), Dataplex, BigQuery, and Vector Search.
• Build batch and streaming ingestion pipelines that keep the graph and catalog current as source systems change.
• Implement data quality checks, schema discovery, and the metadata catalog, surfacing issues to the Architect and Data Domain SME.
• Capture and maintain data lineage from source system through ontology mapping to graph representation.
• Support the Architect's structural-ontology mapping by supplying profiled schemas, dependency maps, and sample data.
• Feed clean, well-profiled data to the ML/Applied Scientists for entity-matching and inference model development.
• Implement governance and control-plane requirements at the pipeline level: IAM scoping, encryption, and lineage tracking set by the Architect.
• Monitor pipeline health, performance, and cost across ingestion, profiling, and graph-load jobs.
Core Skills
• Source-system connectivity via BigQuery, Cloud SQL, REST/Apigee, GCS, and Pub/Sub adapters.
• Data profiling: quality assessment, pattern/dependency detection, and lineage capture.
• Graph and search backbone operations on Spanner Graph (or an equivalent property-graph/RDF platform), Dataplex, BigQuery, and Vector Search.
• Batch and streaming pipeline design (Dataflow, Composer, Pub/Sub).
• Metadata catalog and data-quality tooling.
• Pipeline-level governance: IAM scoping, encryption, and lineage instrumentation.
Required Qualifications
• 5+ years in data engineering, including building ingestion and metadata pipelines at scale.
• Strong Python and SQL.
• Hands-on experience with GCP data services: BigQuery, Dataflow, Pub/Sub, Composer, Cloud SQL, GCS.
• Experience with data profiling, lineage, and metadata catalog tooling (e.g., Dataplex or equivalent).
• Working familiarity with a property graph or RDF platform — Spanner Graph, Neo4j, Amazon Neptune, TigerGraph, JanusGraph, or an RDF/SPARQL store. Spanner Graph itself is not required; Cypher, Gremlin, or SPARQL query experience is an accepted equivalent and ramps up quickly.
Preferred Qualifications
• Direct hands-on experience with Spanner Graph specifically.
• Telecom OSS/BSS experience; TM Forum SID/eTOM familiarity.
• Apigee or another API gateway for source connectivity.
• GCP Data Engineer certification.
Tools & Technologies
BigQuery, Cloud SQL, REST/Apigee, GCS, Pub/Sub, Dataflow, Composer, Dataplex, Spanner Graph (or Neo4j/Neptune/TigerGraph/RDF-SPARQL equivalent), Vector Search, Python, SQL
Salary and Other Compensation:
Applications will be accepted until Dec 06, 2026.
The annual salary for this position is between $80,000 - $140,000 depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
- Medical/Dental/Vision/Life Insurance
- Paid holidays plus Paid Time Off
- 401(k) plan and contributions
- Long-term/Short-term Disability
- Paid Parental Leave
- Employee Stock Purchase Plan
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
