Cognizant is seeking an experienced GCP Data Engineer to design, build, and operate connectivity, metadata/profiling management, and graph and search platforms that support enterprise ontology and knowledge management. The role focuses on transforming operational and master data into governed, lineage-tracked, and queryable knowledge assets, including batch and streaming ingestion on Google Cloud Platform.
Responsibilities
- Design, develop, and maintain connectivity solutions for enterprise data sources.
- Build adapters and integration frameworks supporting: BigQuery, Cloud SQL, REST APIs, Apigee, Google Cloud Storage (GCS), and Pub/Sub.
- Establish scalable and reliable ingestion patterns for operational, transactional, and master data systems.
- Support API-based integrations across enterprise applications and data platforms.
- Profile enterprise data to assess data quality, completeness, statistical patterns, dependencies, data relationships, and source system characteristics.
- Develop data discovery frameworks that support ontology and semantic model development.
- Build metadata management processes supporting data governance, traceability, and analytics.
- Surface data quality issues and metadata findings to architecture and business teams.
- Design and operate the enterprise Knowledge Core for graph-based data exploration and search.
- Implement graph and knowledge management platforms using: Spanner Graph, Neo4j, Amazon Neptune, TigerGraph, RDF/SPARQL technologies, and equivalent graph platforms.
- Support graph data modeling, relationship management, and semantic search capabilities.
- Enable enterprise-scale graph analytics and knowledge discovery use cases.
- Build and maintain batch and real-time data pipelines that continuously synchronize source data with graph and catalog platforms.
- Design ingestion architectures utilizing Dataflow, Apache Beam, Pub/Sub, Cloud Composer, and event-driven architectures.
- Ensure pipelines remain scalable, resilient, and cost-efficient, including near real-time updates across ontology and knowledge graph environments.
- Implement automated data quality controls and validation frameworks, including schema discovery and metadata catalog capabilities.
- Capture and maintain end-to-end data lineage from source systems through graph and ontology representations.
- Establish governance controls including IAM policies, encryption standards, metadata tracking, and lineage instrumentation.
- Partner with architecture and governance teams to ensure compliance with enterprise standards.
- Support ontology mapping activities by providing profiled schemas, data dependency maps, sample data sets, and metadata context.
- Deliver curated and well-profiled datasets supporting machine learning and entity-resolution initiatives.
- Collaborate with data scientists and applied AI teams to improve data quality and knowledge graph accuracy, including graph-powered AI use cases and inference capabilities.
- Monitor platform health, ingestion jobs, graph-processing workloads, and metadata services; troubleshoot issues and implement preventative solutions.
- Optimize performance, scalability, and operational efficiency across the platform stack, and manage cost optimization initiatives across cloud infrastructure and processing workloads.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or a related discipline, or equivalent work experience.
- 5+ years of experience in Data Engineering or Data Platform Engineering.
- Proven experience building large-scale ingestion, metadata, and data management solutions.
- Strong expertise in Python and SQL.
- Hands-on experience with Google Cloud Platform (GCP), including BigQuery, Dataflow, Pub/Sub, Cloud Composer, Cloud SQL, and Google Cloud Storage (GCS).
- Experience implementing data profiling, data lineage, metadata management, and data quality frameworks.
- Experience with graph technologies including one or more of: Spanner Graph, Neo4j, Amazon Neptune, TigerGraph, JanusGraph, and RDF/SPARQL platforms.
- Experience writing graph queries using Cypher, Gremlin, SPARQL, or equivalent graph query languages.
- Strong understanding of data governance and metadata management principles.
- Excellent troubleshooting, analytical, and problem-solving skills.
Technical Expertise
Candidates should demonstrate expertise in: Google Cloud Platform (GCP), BigQuery, Cloud SQL, Dataflow, Pub/Sub, Cloud Composer, Dataplex, Spanner Graph, Neo4j, Amazon Neptune, TigerGraph, RDF/SPARQL, metadata management, data lineage, data quality, knowledge graphs, semantic search, vector search, Python, SQL, API integration, and data governance.
Technologies
- Google Cloud Platform (GCP), BigQuery, Cloud SQL, REST APIs, Apigee, Google Cloud Storage (GCS), Pub/Sub
- Dataflow, Apache Beam, Cloud Composer
- Spanner Graph, Neo4j, Amazon Neptune, TigerGraph, RDF/SPARQL technologies, JanusGraph
- Cypher, Gremlin, SPARQL
- Dataplex, Knowledge Graphs, Semantic Search, Vector Search
- API Integration, Data Lineage, Metadata Management, Data Quality, Event-Driven Architectures
- IAM Policies, Encryption Standards
Salary and Other Compensation
The annual salary for this position is anticipated to be between $100,000 and $120,000 USD, depending on experience, qualifications, geographic location, and other factors permitted by law. In addition to base salary, the position may be eligible for an annual performance-based bonus, merit-based compensation increases, and employee referral bonuses where applicable.
Benefits
- Medical, Dental, and Vision Insurance
- Health Savings Account (HSA) and Flexible Spending Accounts (FSA)
- Life Insurance and AD& D Coverage
- Short-Term and Long-Term Disability Insurance
- Paid Time Off (PTO) and Company Holidays
- 401(k) Plan with Company Contributions (subject to eligibility)
- Employee Stock Purchase Plan (where available)
- Employee Assistance Program (EAP)
- Parental Leave and Family Care Benefits
- Tuition Reimbursement and Professional Development Programs
- Access to Learning, Certification, and Career Development Opportunities
Work Model
- Fully remote within the United States.
- Occasional travel may be required for client workshops, planning sessions, architecture reviews, and strategic initiatives.
Preferred Qualifications
- Hands-on experience with Spanner Graph.
- Experience within telecommunications environments.
- Knowledge of OSS/BSS Systems, TM Forum SID, and eTOM Frameworks.
- Experience with Apigee or enterprise API management platforms.
- Google Cloud Professional Data Engineer Certification.
- Experience building semantic search, knowledge graph, or ontology-based solutions.
- Familiarity with vector search technologies and retrieval architectures.
- Experience supporting AI, knowledge management, or graph-powered analytics initiatives.
Role Location
Phoenix, AZ (remote)
Why Cognizant
- Build next-generation knowledge graph and ontology platforms.
- Work with graph, metadata, cloud, and AI technologies.
- Collaborate with architects, data scientists, and platform engineering teams on enterprise-scale initiatives.
- Gain exposure to advanced semantic search, vector search, and AI-powered knowledge management solutions.
- Access learning, cloud certifications, and career development programs.
- Join a global organization committed to innovation, engineering excellence, and digital transformation.
