Google Cloud Platform Data Engineer (Looking For W2 Candidate Only)

Job Title: Google Cloud Platform Data Engineer (Looking For W2 Candidate Only)
Location: Dallas, TX, Ashburn, VA

Job Description:

We are looking for an experienced Google Cloud Platform Data Engineer with strong hands-on experience in Google Cloud Platform (Google Cloud Platform), Apache Airflow, and BigQuery. The ideal candidate will be responsible for designing, developing, implementing, and maintaining scalable data pipelines and data engineering solutions.

The candidate should have expertise in building ETL/ELT workflows, managing large datasets, optimizing BigQuery queries, and orchestrating data pipelines using Apache Airflow.

Key Responsibilities

Design, develop, and maintain scalable data pipelines using Google Cloud Platform.

Build and manage ETL/ELT workflows using Apache Airflow.

Develop complex SQL queries, stored procedures, and data transformations in BigQuery.

Implement and maintain data ingestion processes from multiple sources into Google Cloud Platform.

Work with Google Cloud Platform services such as Cloud Storage (GCS), Dataflow, Pub/Sub, and Cloud Composer.

Develop and schedule automated workflows using Airflow DAGs.

Monitor, troubleshoot, and optimize data pipelines for performance and reliability.

Perform BigQuery query optimization, partitioning, clustering, and cost optimization.

Implement data quality checks, validation, and error-handling mechanisms.

Collaborate with data architects, analysts, and other engineering teams.

Ensure data security, governance, and compliance standards.

Required Skills

Strong hands-on experience with Google Cloud Platform (Google Cloud Platform).

Expertise in BigQuery, including advanced SQL and query optimization.

Hands-on experience with Apache Airflow and DAG development.

Experience with Cloud Composer for workflow orchestration.

Strong Python programming skills.

Experience developing ETL/ELT data pipelines.

Good understanding of data warehousing and data modeling concepts.

Experience with Google Cloud Storage (GCS).

Knowledge of Dataflow, Pub/Sub, and other Google Cloud Platform services.

Experience with Git and CI/CD processes.

Preferred Qualifications

Google Cloud Professional Data Engineer certification.

Experience with Spark / PySpark.

Knowledge of Terraform and infrastructure automation.

Experience with data lake and lakehouse architectures.

Familiarity with monitoring and logging tools in Google Cloud Platform.