5 days ago
Base Salary
$100k - $120k/yr
Responsibilities
- Design and maintain enterprise data connectivity, adapters, API integrations, and scalable ingestion frameworks.
- Build batch and real-time pipelines that synchronize operational, transactional, and master data with graph and catalog platforms.
- Profile enterprise data and develop metadata, discovery, governance, lineage, and data quality capabilities.
- Design and operate graph and knowledge management platforms supporting graph modeling, semantic search, analytics, and knowledge discovery.
- Implement data quality controls, schema discovery, IAM, encryption, metadata tracking, and end-to-end lineage instrumentation.
- Provide profiled schemas, dependency maps, sample datasets, and metadata context for ontology mapping and semantic model development.
- Deliver curated datasets for machine learning and entity-resolution initiatives and collaborate with data scientists and applied AI teams.
- Monitor platform health, ingestion jobs, graph-processing workloads, and metadata services while optimizing reliability, performance, scalability, and cost.
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.
- Experience building large-scale ingestion, metadata, and data management solutions.
- Strong expertise in Python and SQL.
- Hands-on Google Cloud experience with BigQuery, Dataflow, Pub/Sub, Cloud Composer, Cloud SQL, and Google Cloud Storage.
- Experience implementing data profiling, data lineage, metadata management, and data quality frameworks.
- Experience with one or more graph technologies, including Spanner Graph, Neo4j, Amazon Neptune, TigerGraph, JanusGraph, or 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.
- Preferred qualifications include Spanner Graph experience, telecommunications experience, OSS/BSS systems knowledge, TM Forum SID, eTOM frameworks, Apigee, Google Cloud Professional Data Engineer Certification, semantic search, knowledge graph or ontology solutions, vector search, retrieval architectures, and AI or graph-powered analytics initiatives.
Benefits
- Fully remote within the United States, with occasional travel for client workshops, planning sessions, architecture reviews, and strategic initiatives.
- Medical, dental, and vision insurance plus health savings and flexible spending accounts.
- Life insurance, AD&D coverage, and short- and long-term disability insurance.
- Paid time off and company holidays.
- 401(k) plan with company contributions, subject to eligibility.
- Employee stock purchase plan where available.
- Employee assistance program, parental leave, and family care benefits.
- Tuition reimbursement, professional development, learning, certification, and career development programs.
- Potential eligibility for annual performance bonuses, merit-based compensation increases, and applicable employee referral bonuses.
Tech Stack
Categories
Data Engineering
About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.