GCP Certified Data Engineer

GCP Data Engineer

Location:
Atlanta, GA (On-site/Hybrid as applicable)

Summary

We are seeking a highly skilled
GCP Data Engineer
to design, build, and optimize cloud-native data pipelines and analytics solutions on Google Cloud Platform. The ideal candidate has strong experience with
Python
,
BigQuery
,
Cloud Data Fusion
, and core GCP services such as
Cloud Composer
,
Cloud Storage
,
Cloud Functions
, and
Pub/Sub
. This role requires a strong foundation in
data warehousing concepts
and scalable data engineering practices.

Responsibilities

• Design, develop, and maintain robust ETL/ELT pipelines on
  Google Cloud Platform
  .
• Build and optimize data workflows using
  Cloud Data Fusion
  ,
  BigQuery
  , and
  Cloud Composer
  .
• Write efficient and maintainable
  Python
  code to support data ingestion, transformation, and automation.
• Develop optimized
  BigQuery SQL
  for analytics, reporting, and large-scale data modeling.
• Utilize GCP services such as
  Cloud Storage
  ,
  Pub/Sub
  , and
  Cloud Functions
  to build event-driven and scalable data solutions.
• Ensure data quality, governance, and reliability across all pipelines.
• Collaborate with cross-functional teams to deliver clean, trusted, production-ready datasets.
• Monitor, troubleshoot, and resolve performance issues in cloud data pipelines and workflows.

Must-Have Skills

• Strong experience with
  GCP BigQuery
  (data modeling, SQL development, performance tuning).
• Proficiency in
  Python
  for data engineering and pipeline automation.
• Hands-on experience with
  Cloud Data Fusion
  for ETL/ELT development.
• Working experience with key GCP services:
• Cloud Composer
• Cloud Storage
• Cloud Functions
• Pub/Sub
• Strong understanding of
  data warehousing concepts
  , star/snowflake schemas, and best practices.
• Solid understanding of cloud data architecture and distributed processing.

Good-to-Have Skills

• Experience with
  Vertex AI
  for ML pipeline integration or model deployment.
• Familiarity with
  Dataproc
  (Spark/Hadoop) for large-scale processing.
• Knowledge of CI/CD workflows, Git, and DevOps best practices.
• Experience with Cloud Logging/Monitoring tools.