CoSourcing Partners

CoSourcing Partners

Google Cloud Platform Data Engineer

Chicago, Illinois, USA · full-time

Sponsorship not specifiedDetected 45 days ago
PythonGitSQLBigQueryGCPCloud PlatformsCI/CDGitHub ActionsJenkinsMachine LearningdbtData EngineeringCommunicationCollaborationProblem Solving

About the role

  • We are seeking a highly skilled Google Cloud Platform Data Engineer to design, develop, and optimize scalable data solutions on Google Cloud Platform (Google Cloud Platform).
  • The ideal candidate will have strong expertise in building robust batch and streaming pipelines, implementing modern data architectures, and enabling reliable, high-quality data platforms for analytics, reporting, and machine learning use cases.

Responsibilities

  • Data Engineering & Pipeline Development Design, build, and optimize scalable batch and real-time (streaming) data pipelines using Google Cloud Platformnative services.
  • Develop and maintain data ingestion frameworks leveraging tools such as Pub/Sub, Dataflow, and Cloud Storage.
  • Implement data transformation pipelines using BigQuery, dbt, and Python-based workflows.
  • Data Modeling & Architecture Design and implement high-performance data models for cloud-based data lakes, data warehouses, and analytics platforms.
  • Optimize data schemas and partitioning strategies in BigQuery for performance and cost efficiency.
  • Support modern architectures such as medallion (bronze/silver/gold) layers and lakehouse patterns.
  • Develop scalable data processing logic using Python and/or Apache Beam.
  • Build reusable, modular, and maintainable code for data workflows.
  • Data Quality, Observability & Reliability Implement and maintain data quality checks, validation rules, and anomaly detection frameworks.
  • ETL/ELT Modernization Support migration and modernization efforts from legacy ETL tools (e.g., Talend) to Google Cloud Platform-native ELT frameworks (dbt).

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.
  • 4+ years of experience in data engineering or data platform development.
  • Hands-on experience with Google Cloud Platform (Google Cloud Platform) services: BigQuery Dataflow Pub/Sub Cloud Storage Strong proficiency in SQL and Python.
  • Experience with dbt (Data Build Tool) or similar ELT frameworks.
  • Familiarity with Talend or other ETL tools and migration to cloud-native solutions.
  • Knowledge of data lakehouse architectures and modern data stack.
  • Experience with CI/CD tools (e.g., GitHub Actions, Cloud Build, Jenkins).

Nice to have

  • Ensure efficient handling of large-scale structured and unstructured datasets.
  • Development & Coding Write advanced SQL queries for transformation, validation, and analytics.
  • Enable data observability through monitoring, logging, and alerting mechanisms.
  • Ensure highly reliable data pipelines with fault tolerance and error handling strategies.
  • Translate business requirements into scalable data solutions.

Benefits

  • Collaboration & Stakeholder Engagement Collaborate with data architects, business analysts, and machine learning teams to deliver trusted datasets.
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