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GCP Data Engineer with AI/ML Integration & MLOps, Irving, TX 75039 (Onsite) at Irving, Texas, USA
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Role: GCP Data Engineer with AI/ML Integration & MLOps

Location: Irving, TX 75039 (Onsite)

Experience: 10+ Years

Job Type: Contract/W2

Duration: Long Term

Interview Mode: L1 Virtual | In-person client interview

Rate on C2C: $70/Hr

Must have: Dataplex exp

Overview

We are seeking a GCP Data Engineer with deep, hands-on architectural and development

Experience in Google Cloud Platforms 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.

Required Qualifications

7+ years of dedicated
Data Engineering experience, with at least 3+ years focused exclusively on the
Google Cloud Platform (GCP).

Expert-level knowledge of BigQuery architecture, advanced SQL, analytical functions, query profiling, and optimization techniques.

Proven experience utilizing BigLake
for multi-cloud or lakehouse architectures, managing open-source formats (e.g., Apache Iceberg/Parquet),
and enforcing unified security policies.

Deep understanding of GCS storage classes, object lifecycle management, and
optimizing GCS for big data workloads.

Hands-on experience with Vertex AI pipelines, endpoints, feature stores, or deploying ML models into scalable data environments.

Advanced proficiency in Python and SQL.

Familiarity with Java, Scala, or Go is a plus.

Experience with orchestration tools (e.g., Apache Airflow, Cloud Composer)
and modern CI/CD pipelines (e.g., GitHub Actions, Terraform, Cloud Build).

GCP Certifications: Google Cloud Certified - Professional Data Engineer or Professional Machine Learning Engineer.

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.

AI/ML Integration & MLOps:

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.

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.

Looking forward to qualified submissions only.

Thanks & Regards

Nikhila Gujjarlamudi

Ph: +1 615-857-(6282) |
Email: [email protected]

LinkedIn:
linkedin.com/in/nikhilagujjarlamudi

Website:
https://tror.ai

Address: 401 Ronan Way, Spring Hill, 37174

Keywords: continuous integration continuous deployment artificial intelligence machine learning golang wtwo trade national Idaho Tennessee Texas
GCP Data Engineer with AI/ML Integration & MLOps, Irving, TX 75039 (Onsite)
[email protected]
http://bit.ly/4ey8w48
https://jobs.nvoids.com/job_details.jsp?id=3320739&uid=190105d6130643388f5014182fa86af2
[email protected]
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09:04 PM 23-Apr-26


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