[Upgrade to PRO to see contact]
H1b Workable
Relocation is Fine
Role : GCP Data Engineer with AI/ML Integration & MLOps
Location : Irving, Texas 75039Β (100% onsite)
Hire type : Contract
Interview Mode : 1 Video interview andΒ client interview will be in personΒ from any one of the Client office In usa
ImplementationΒ partner - **********
End Client - Banking Client
Experience: 9+
Β
Overview
We are seeking a GCP Data Engineer with deep, hands-on architectural and development
experience in Google Cloud Platformβs big data ecosystem. You will be responsible for
designing, building, and optimizing a modern data lakehouse architecture. Your primary focus
will be leveraging BigLake, BigQuery, Google Cloud Storage (GCS), and Vertex AI to create
seamless, scalable data pipelines and machine learning integrations that drive business
intelligence and predictive analytics.
Β
Key Responsibilities
Lakehouse 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) and
data 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 utilizing
clustering, partitioning, materialized views, and slot capacity management.
Β
AI/ML Integration & MLOps:
Β Collaborate with Data Scientists to operationalize machine learning models using
Vertex AI.
Build robust data pipelines to feed Vertex AI Feature Store, manage model
training workflows and deploy ML models into production.
Utilize Big Query ML (BQML) for in-database predictive modeling and analytics
where appropriate.
Β
Data Pipeline Engineering:
Design, develop, and orchestrate batch and streaming data pipelines (using tools
like Dataflow, Dataproc, or Cloud Composer/Airflow) to ingest data from diverse
sources 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 big
data stack.
Mentor junior engineers and lead code/architecture reviews.
Β
Required Qualifications
Experience: 5+ years of dedicated Data Engineering experience, with at least 3+ years
focused exclusively on the Google Cloud Platform (GCP).
Β
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 lakehouse
architectures, managing open-source formats (e.g., Apache Iceberg/Parquet),
and enforcing unified security policies.
GCS: Deep understanding of GCS storage classes, object lifecycle management,