Jobs via Dice
Data Engineer Google Cloud Platform & Vertex AI
Jobs via Dice, Alpharetta, Georgia, United States, 30239
Data Engineer – Hexacorp
No remote, onsite only in Alpharetta, GA.
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Hexacorp, is seeking a
Data Engineer with expertise in Google Cloud Platform and Vertex AI
to design, build, and optimize
data pipelines
supporting machine learning and analytics. The role requires hands‑on experience in
data engineering, ML‑ready data preparation, and integration with Vertex AI pipelines
for scalable AI/ML model development.
Key Responsibilities
Design and implement scalable ETL/ELT pipelines using Dataflow, Dataproc, BigQuery, and Pub/Sub.
Collaborate with Data Scientists and MLOps teams to prepare and serve ML-ready datasets for training and inference on Vertex AI.
Integrate structured, semi-structured, and unstructured data from multiple sources into Google Cloud Platform data lake/warehouse.
Build feature pipelines and manage Vertex AI Feature Store.
Implement data quality checks, governance, and lineage in pipelines.
Optimize storage and compute costs across Google Cloud Platform services.
Support real-time and batch data processing for ML pipelines and analytics.
Ensure security, compliance, and monitoring of data pipelines.
Required Skills & Experience
Strong expertise with Google Cloud Platform data services: BigQuery, Dataflow (Apache Beam), Pub/Sub, Dataproc, Cloud Storage, Composer (Airflow).
Experience working with Vertex AI pipelines and Feature Store.
Strong SQL and Python programming skills.
Hands‑on experience with data modeling, partitioning, performance optimization.
Proficiency with CI/CD for data pipelines (Cloud Build, Jenkins, GitHub Actions).
Familiarity with Terraform/IaC for Google Cloud Platform environment setup.
Knowledge of containerization (Docker, Kubernetes) for pipeline orchestration.
Preferred Qualifications
Google Cloud Platform Certifications: Professional Data Engineer or Professional Machine Learning Engineer.
Experience with Kubeflow, MLflow, or TFX for pipeline integration.
Exposure to data observability tools (Dataplex, Great Expectations, dbt).
Strong understanding of AI/ML lifecycle workflows and model deployment integration.
Why Join Us?
Work on data & AI-driven solutions at scale.
Collaborate with a global team of Data Engineers, MLOps Engineers, and Data Scientists.
Opportunity to grow into a Lead Data Engineer / MLOps Architect role.
Job Details
Seniority level: Entry level
Employment type: Full-time
Job function: Information Technology
Industries: Software Development
Location: Alpharetta, GA
Salary: $110,000.00 - $130,000.00
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Dice is the leading career destination for tech experts at every stage of their careers. Our client, Hexacorp, is seeking a
Data Engineer with expertise in Google Cloud Platform and Vertex AI
to design, build, and optimize
data pipelines
supporting machine learning and analytics. The role requires hands‑on experience in
data engineering, ML‑ready data preparation, and integration with Vertex AI pipelines
for scalable AI/ML model development.
Key Responsibilities
Design and implement scalable ETL/ELT pipelines using Dataflow, Dataproc, BigQuery, and Pub/Sub.
Collaborate with Data Scientists and MLOps teams to prepare and serve ML-ready datasets for training and inference on Vertex AI.
Integrate structured, semi-structured, and unstructured data from multiple sources into Google Cloud Platform data lake/warehouse.
Build feature pipelines and manage Vertex AI Feature Store.
Implement data quality checks, governance, and lineage in pipelines.
Optimize storage and compute costs across Google Cloud Platform services.
Support real-time and batch data processing for ML pipelines and analytics.
Ensure security, compliance, and monitoring of data pipelines.
Required Skills & Experience
Strong expertise with Google Cloud Platform data services: BigQuery, Dataflow (Apache Beam), Pub/Sub, Dataproc, Cloud Storage, Composer (Airflow).
Experience working with Vertex AI pipelines and Feature Store.
Strong SQL and Python programming skills.
Hands‑on experience with data modeling, partitioning, performance optimization.
Proficiency with CI/CD for data pipelines (Cloud Build, Jenkins, GitHub Actions).
Familiarity with Terraform/IaC for Google Cloud Platform environment setup.
Knowledge of containerization (Docker, Kubernetes) for pipeline orchestration.
Preferred Qualifications
Google Cloud Platform Certifications: Professional Data Engineer or Professional Machine Learning Engineer.
Experience with Kubeflow, MLflow, or TFX for pipeline integration.
Exposure to data observability tools (Dataplex, Great Expectations, dbt).
Strong understanding of AI/ML lifecycle workflows and model deployment integration.
Why Join Us?
Work on data & AI-driven solutions at scale.
Collaborate with a global team of Data Engineers, MLOps Engineers, and Data Scientists.
Opportunity to grow into a Lead Data Engineer / MLOps Architect role.
Job Details
Seniority level: Entry level
Employment type: Full-time
Job function: Information Technology
Industries: Software Development
Location: Alpharetta, GA
Salary: $110,000.00 - $130,000.00
#J-18808-Ljbffr