> Markdown version of [/jobs/ext/4632620-sr-gcp-data-engineer-remote](https://www.wearedevelopers.com/jobs/ext/4632620-sr-gcp-data-engineer-remote). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. GCP Data Engineer (Remote) - **Company:** Cognizant Technology Solutions Corporation - **Location:** Phoenix, AZ, United States - **Experience:** Expert - **Salary:** $80,000 - $140,000 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), BigQuery, Data Validation, Information Engineering, Data Profiling, Data Flow Control, Identity and Access Management, Python (Programming Language), Metadata, Neo4j, Search Technologies, SPARQL, SQL Databases, TigerGraph, Data Ingestion, Apigee, OSS/BSS, Data Management, Api Gateway - **Published:** November 8, 2026 - **Apply:** https://www.phoenixjobs.com/job.asp?id=3505241149&tx=JK10599LFU&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * 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., * 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 ## Description * 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.