Senior Google Cloud Data Engineer - BigQuery & Pipelines

MACHINE LEARNING TECHNOLOGIES LLC; Atlanta (GA); On-site; USD 83,000 - 131,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC is seeking a Sr. Google Cloud Platform Data Engineer/Architect to design, build, and optimize data pipelines and analytics solutions in the cloud.

You will work with BigQuery, Dataflow, Pub/Sub, and IAM to implement scalable data architectures and ensure performance and security. Ideal candidates have 8+ years in data engineering, strong SQL/Python, and hands-on GCP experience.

Qualifications

• Bachelor's degree in CS/IT or related field.
• 8+ years data engineering, cloud experience preferred.
• 3+ years hands-on with Google Cloud Platform services: BigQuery, Cloud Storage, Dataflow, Pub/Sub, IAM.
• Proficient in SQL, Python, and Linux scripting.
• Experience with ETL tools: Datastage, Informatica, SSIS.
• Knowledge of data modeling and data warehousing concepts.

Responsibilities

• Develop ETL/ELT processes to load data into BigQuery and other targets.
• Build data models, data warehouses, and data lakes for analytics.
• Design scalable, secure data pipelines on Google Cloud Platform using Dataflow, Pub/Sub, Cloud Run.
• Optimize BigQuery queries, partitioning, and cost optimization.
• Integrate data from on-premises and cloud systems using Cloud Storage and APIs.
• Collaborate with DevOps to automate deployments with Terraform and CI/CD.
• Ensure security/compliance with IAM, encryption, and network controls.
• Partner with analysts/scientists to deliver high-quality data solutions.

Skills

ETL/ELT development

SQL

Python

Linux scripting

Data modeling

Data warehousing

CI/CD

Cost optimization

Education

Bachelor's degree in Computer Science / Information Technology

Tools

Terraform

Datastage

Informatica

SSIS

Git

Cloud Build

Job description

MACHINE LEARNING TECHNOLOGIES LLC is seeking a Sr. Google Cloud Platform Data Engineer/Architect to design, build, and optimize data pipelines and analytics solutions in the cloud.

You will work with BigQuery, Dataflow, Pub/Sub, and IAM to implement scalable data architectures and ensure performance and security. Ideal candidates have 8+ years in data engineering, strong SQL/Python, and hands-on GCP experience.