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# Data Engineer Google Cloud Platform

- **Company:** Projas Technologies, LLC
- **Location:** Oakland, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Big Data, BigQuery, Continuous Integration, Information Engineering, Data Governance, Data Integrity, Extract Transform Load (ETL), Dataspaces, Data Systems, Data Flow Control, Python (Programming Language), DataOps, SQL Databases, Data Streaming, Google Cloud, Apache Spark, Git, Pyspark, Infrastructure Automation Frameworks, Data Lineage, Operational Systems, Terraform, Stream Processing, Software Version Control, Data Pipelines
- **Published:** July 17, 2026
- **Apply:** https://www.dice.com/job-detail/f5c3a835-2dcf-4d15-b84b-341d992d865f

## About the Role

We are seeking a highly skilled and motivated Senior Data Engineer to join our data platform team. The ideal candidate will have hands-on experience with Google Cloud Platform (Google Cloud Platform) services, including BigQuery, Cloud Composer, Dataflow, and Apache Spark/PySpark, along with a strong understanding of data quality frameworks using Monte Carlo., * 4+ years of experience in data engineering or related field

 * Strong proficiency in Google Cloud Platform services: BigQuery, Dataflow, Cloud Composer
 * Expertise in Apache Spark and PySpark
 * Experience with Monte Carlo or similar data observability tools
 * Proficiency in SQL and Python
 * Familiarity with CI/CD pipelines and version control (e.g., Git)
 * Excellent problem-solving and communication skills, * Experience with real-time data processing and streaming
 * Knowledge of data modeling and warehousing best practices
 * Familiarity with Terraform or Infrastructure as Code (IaC) tools
 * Certification in Google Cloud Platform Data Engineering is a plus

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## Description

You will be responsible for designing, building, and maintaining scalable data pipelines, ensuring high data quality and reliability across our analytics and operational systems., * Design and implement scalable ETL/ELT pipelines using Dataflow, Composer, and Spark/PySpark

 * Optimize and manage large-scale datasets in BigQuery
 * Monitor and improve data quality using Monte Carlo
 * Collaborate with data scientists, analysts, and business stakeholders to deliver reliable data solutions
 * Automate workflows and orchestrate pipelines using Apache Airflow (via Composer)
 * Ensure data governance, lineage, and observability across the data ecosystem
 * Troubleshoot and resolve data pipeline issues in production environments


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