{"id":3896810,"url":"https://alion.io/job/cognizant-sr-gcp-data-engineer-remote","title":"Sr. GCP Data Engineer (Remote)","company":{"id":85,"name":"Cognizant","domain":"cognizant.com","url":"https://alion.io/company/cognizant","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Cognizant Careers","truth_index":{"grade":"A","score":87,"open_postings":179,"ghost_share":0,"stale_share":0.486,"repost_share":0.056,"time_to_fill_p50_days":23,"computed_at":"2026-11-08T05:47:12Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Phoenix, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":80000,"max":140000,"currency":"USD","period":"year","gross":null,"usd_annual":140000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Amazon Neptune","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google Cloud Spanner","optional":false},{"name":"IAM","optional":false},{"name":"Neo4j","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"API Gateway","optional":true}],"status":"live","first_seen_at":"2026-11-06T14:44:33Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-08T17:03:21Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Role Summary\nBuild the connectivity, profiling, and graph/search backbone that the ontology runs on - turning raw source systems into clean, lineage-tracked, query able knowledge.\nKey Responsibilities\nOwn 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.\nOwn data profiling and inference: profile source data for quality, statistical patterns, dependencies, and lineage ahead of ontology mapping.\nStand 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.\nBuild batch and streaming ingestion pipelines that keep the graph and catalog current as source systems change.\nImplement data quality checks, schema discovery, and the metadata catalog, surfacing issues to the Architect and Data Domain SME.\nCapture and maintain data lineage from source system through ontology mapping to graph representation.\nSupport the Architect's structural-ontology mapping by supplying profiled schemas, dependency maps, and sample data.\nFeed clean, well-profiled data to the ML/Applied Scientists for entity-matching and inference model development.\nImplement governance and control-plane requirements at the pipeline level: IAM scoping, encryption, and lineage tracking set by the Architect.\nMonitor pipeline health, performance, and cost across ingestion, profiling, and graph-load jobs.\nCore Skills\nSource-system connectivity via BigQuery, Cloud SQL, REST/Apigee, GCS, and Pub/Sub adapters.\nData profiling: quality assessment, pattern/dependency detection, and lineage capture.\nGraph and search backbone operations on Spanner Graph (or an equivalent property-graph/RDF platform), Dataplex, BigQuery, and Vector Search.\nBatch and streaming pipeline design (Dataflow, Composer, Pub/Sub).\nMetadata catalog and data-quality tooling.\nPipeline-level governance: IAM scoping, encryption, and lineage instrumentation.\nRequired Qualifications\n5+ years in data engineering, including building ingestion and metadata pipelines at scale.\nStrong Python and SQL.\nHands-on experience with GCP data services: BigQuery, Dataflow, Pub/Sub, Composer, Cloud SQL, GCS.\nExperience with data profiling, lineage, and metadata catalog tooling (e.g., Dataplex or equivalent).\nWorking 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.\nPreferred Qualifications\nDirect hands-on experience with Spanner Graph specifically.\nTelecom OSS/BSS experience; TM Forum SID/eTOM familiarity.\nApigee or another API gateway for source connectivity.\nGCP Data Engineer certification.\nTools & Technologies\nBigQuery, Cloud SQL, REST/Apigee, GCS, Pub/Sub, Dataflow, Composer, Dataplex, Spanner Graph (or Neo4j/Neptune/TigerGraph/RDF-SPARQL equivalent), Vector Search, Python, SQL\nSalary and Other Compensation:\nApplications will be accepted until Dec 06, 2026.\nThe annual salary for this position is between $80,000 - $140,000 depending on experience and other qualifications of the successful candidate.\nThis position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.\nBenefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:\nMedical/Dental/Vision/Life Insurance\nPaid holidays plus Paid Time Off\n 401(k) plan and contributions\nLong-term/Short-term Disability\nPaid Parental Leave\nEmployee Stock Purchase Plan\nDisclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. 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