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# Google Cloud Platform Data Engineer

- **Company:** Relanto, Inc.
- **Location:** San Francisco, CA, United States
- **Contract:** Permanent contract
- **Skills:** Airflow, Big Data, BigQuery, Cloud Storage, Code Review, Continuous Integration, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Distributed Computing Environment, Python (Programming Language), Operational Databases, Standard Sql, Cloudera, SQL Databases, Data Logging, Google Cloud, Cloud Platform System, Git, Containerization, Pyspark, Kubernetes, Information Technology, Apache Kafka, Terraform, Data Pipelines, Docker
- **Published:** August 14, 2026
- **Apply:** https://www.dice.com/job-detail/e3a69d7e-e34b-46b2-989b-44ea5542a86e

## About the Role

* Strong hands-on experience with Python and SQL
 * Experience with PySpark and distributed data processing
 * Good knowledge of BigQuery and Google Cloud Platform services
 * Experience with Apache Airflow for orchestration
 * Hands-on experience with dbt for data transformation and modeling
 * Understanding of ETL/ELT frameworks and data warehousing concepts

Familiarity with Google Cloud Platform services such as:

 * BigQuery
 * Cloud Storage
 * Dataproc
 * Composer
 * Pub/Sub
 * Experience with Git and CI/CD practices
 * Strong analytical and problem-solving skills

Good to Have

 * Exposure to streaming pipelines using Kafka or Pub/Sub
 * Understanding of data governance and security concepts
 * Experience with Terraform or Infrastructure as Code
 * Knowledge of containerization (Docker/Kubernetes)

Preferred Qualification

 * Bachelor's degree in Computer Science, Engineering, or related field
 * Google Cloud Platform certification is a plus

## Description

We are looking for a skilled Google Cloud Platform Data Engineer with proven experience in building and maintaining scalable data pipelines and cloud-based data platforms on Google Cloud Platform (Google Cloud Platform). The ideal candidate should have hands-on expertise in Python, SQL, PySpark, BigQuery, Airflow, and modern ETL/ELT frameworks.

The role involves working closely with analytics, business, and engineering teams to enable reliable and scalable data solutions., * Design, develop, and maintain scalable data pipelines using Python and PySpark

 * Build and optimize ETL/ELT workflows using Apache Airflow
 * Develop data transformation models and workflows using dbt
 * Work with BigQuery for data warehousing, querying, and optimization
 * Write efficient and optimized SQL queries for large-scale data processing
 * Ensure data quality, integrity, and reliability across pipelines
 * Collaborate with Data Analysts, Data Scientists, and business stakeholders for data requirements
 * Monitor and troubleshoot production data workflows and resolve issues proactively
 * Implement best practices for logging, monitoring, testing, and CI/CD
 * Optimize cloud resource usage and cost efficiency on Google Cloud Platform
 * Participate in code reviews and engineering best practices


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