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Senior, specialized GCP lakehouse role at a Fortune 500 retailer reduces applicant density despite brand visibility.
Medium because GCP lakehouse and Spark skills are transferable, but vector DB and retail nuances narrow fit.
High due to explicit 10+ years requirement and mandatory GCP, Delta Lake, Spark, and vector DB expertise.
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Lead and mentor a data engineering team to build and optimize a GCP Data Lakehouse platform with robust architecture and governance.
Own end-to-end design, implementation, and performance tuning of data pipelines and SQL workloads handling structured, semi-structured, and unstructured data at scale.
Collaborate with cross-functional teams and stakeholders to develop scalable data solutions supporting analytics, reporting, machine learning, and ensure secure, compliant data governance.
10+ years experience in data engineering or architecture with proven large-scale pipeline/platform design and deployment.
Strong hands-on expertise in GCP Data Lake technologies, Apache Spark, Delta Lake, PySpark/Scala, and advanced SQL performance tuning.
Experience implementing data governance with GCP Data Lake Unity Catalog, including fine-grained access controls and security compliance.
Work Experience Required: 10+ years; Notice Period: Not explicitly mentioned in the JD.
Experienced senior data architect comfortable leading engineering teams and projects in Agile environments, with excellent cross-functional communication skills.
Deep domain expertise in cloud data platforms (GCP preferred) and big data ecosystems including vector databases for scalable RAG systems and LLM integration.
Proven track record of optimizing ETL jobs for cost and performance, implementing CI/CD for data workflows, and driving continuous platform improvements.