GCP Data Engineer with AI/ML Integration & MLOps

Role : GCP Data Engineer with AI/ML Integration & MLOpsLocation : Irving, Texas 75039 (100% onsite)Hire type : ContractInterview Mode : 1 Video interview and client interview will be in person from any Client officeRate : $65OverviewWe are seeking a GCP Data Engineer with deep, hands-on architectural and developmentexperience in Google Cloud Platform's big data ecosystem. You will be responsible fordesigning, building, and optimizing a modern data lakehouse architecture. Your primary focuswill be leveraging BigLake, BigQuery, Google Cloud Storage (GCS), and Vertex AI to createseamless, scalable data pipelines and machine learning integrations that drive businessintelligence and predictive analytics.Key ResponsibilitiesLakehouse Architecture & Development:Architect and maintain a scalable data lakehouse using Google Cloud Storage(GCS) as the foundational data lake and BigLake to unify data warehouses and data lakes.Implement fine-grained security (row-level and column-level access controls) anddata governance across open file formats (Parquet, Iceberg, ORC) using BigLake.Data Warehousing & Optimization:Design and manage complex, highly scalable data models within Big Query.Perform deep performance tuning and cost optimization of Big Query jobs utilizingclustering, partitioning, materialized views, and slot capacity management.AI/ML Integration & MLOps:Collaborate with Data Scientists to operationalize machine learning models usingVertex AI.Build robust data pipelines to feed Vertex AI Feature Store, manage modeltraining workflows and deploy ML models into production.Utilize Big Query ML (BQML) for in-database predictive modeling and analyticswhere appropriate.Data Pipeline Engineering:Design, develop, and orchestrate batch and streaming data pipelines (using toolslike Dataflow, Dataproc, or Cloud Composer/Airflow) to ingest data from diversesources into GCS and BigQuery.Data Governance & Best Practices:Establish data lifecycle management policies in GCS.Ensure data quality, reliability, and security compliance across the entire GCP bigdata stack.Mentor junior engineers and lead code/architecture reviews.Required QualificationsExperience: 5+ years of dedicated Data Engineering experience, with at least 3+ yearsfocused exclusively on the Google Cloud Platform (GCP).Deep GCP Big Data Expertise:BigQuery: Expert-level knowledge of BigQuery architecture, advanced SQL,analytical functions, query profiling, and optimization techniques.BigLake: Proven experience utilizing BigLake for multi-cloud or lakehousearchitectures, managing open-source formats (e.g., Apache Iceberg/Parquet),and enforcing unified security policies.GCS: Deep understanding of GCS storage classes, object lifecycle management,and optimizing GCS for big data workloads.Vertex AI: Hands-on experience with Vertex AI pipelines, endpoints, featurestores, or deploying ML models into scalable data environments.Programming Skills: Advanced proficiency in Python and SQL. Familiarity with Java,Scala, or Go is a plus.Data Orchestration & CI/CD: Experience with orchestration tools (e.g., Apache Airflow,Cloud Composer) and modern CI/CD pipelines (e.g., GitHub Actions, Terraform, CloudBuild).Preferred/Bonus QualificationsGCP Certifications: Google Cloud Certified - Professional Data Engineer orProfessional Machine Learning Engineer.DISCLAIMER==========This e-mail may contain privileged and confidential information which is the property of Persistent Systems Ltd. It is intended only for the use of the individual or entity to which it is addressed. If you are not the intended recipient, you are not authorized to read, retain, copy, print, distribute or use this message. If you have received this communication in error, please notify the sender and delete all copies of this message. Persistent Systems Ltd. does not accept any liability for virus infected mails.