Lead GCP Data Engineer Dallas, TX

QTechDallas, TX
Onsite

About The Position

We are seeking a Lead GCP Data Engineer for a long-term contract position in Dallas, TX. This role requires onsite presence and is open to W2 candidates only (No C2C). The ideal candidate will have experience leading a team to meet project requirements and deliverables, with a strong background in data warehousing, ETL, and GCP services.

Requirements

  • 9+ years of experience in Data Warehousing.
  • 9+ years of hands-on ETL experience (e.g., Informatica/DataStage).
  • 3+ years of hands-on BigQuery experience.
  • 3+ years of hands-on GCP experience.
  • 9+ years of Teradata hands-on experience.
  • 3+ years of hands-on experience with Google Cloud Platform services like BigQuery, Dataflow, Pub/Sub, and Cloud Storage.
  • 3+ years of hands-on experience building modern data pipelines with GCP platform.
  • 3+ years of experience with Query optimization, data structures, transformation, metadata, dependency, and workload management.
  • 3+ years of experience with SQL, NoSQL.
  • 3+ years of experience in data engineering with a focus on microservices-based data solutions.
  • 3+ years of containerization (Docker, Kubernetes) and CI/CD for data pipeline experience.
  • 3+ years of experience with Python (or a comparable scripting language).
  • 3+ years of experience with Big data and cloud architecture.
  • 3+ years of experience with deployment/scaling of apps on containerized environment (Kubernetes).
  • Excellent oral and written communications skills; ability to interact effectively with all levels within the organization.

Responsibilities

  • Lead a team to meet project requirements and deliverables.
  • Design, build, and maintain modern data pipelines using the GCP platform.
  • Optimize queries, manage data structures, transformations, metadata, dependencies, and workloads.
  • Develop data engineering solutions with a focus on microservices-based data solutions.
  • Implement containerization (Docker, Kubernetes) and CI/CD for data pipelines.
  • Deploy and scale applications on containerized environments (Kubernetes).
  • Communicate effectively with all levels within the organization.
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