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GCP /Python Data Engineer

Cap*** · Atlanta, GA, United States
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Atlanta, GA, United StatesHybrid
Remuneration
Not specified
Location
Atlanta, GA, United States
Visa sponsorship
Sponsors visa

Job summary

Choosing Cap*** means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible.

Benefits

Package to all regular, full-time employees.In the U.And Canada, availableAre determined by local policy and eligibility and may include:Medical, dental, and vision coverage (or provincial healthcare coordination in CRetirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)Life and disability insuranceEmployee assistance programsOtherAs provided by local policy and eligibilityThe Company reserves the right to amend or withdraw compensation programs at any

Qualifications

  • The ideal candidate will have hands-on experience developing batch and real-time data pipelines, working with large-scale datasets, and enabling analytics and AI/ML use cases.
  • Experience with Dataproc (Spark/PySpark) for large-scale processing
  • Familiarity with event-driven architectures
  • Knowledge of Terraform or Infrastructure as Code
  • Understanding of cost optimization (FinOps)
  • Nice to Have
  • Google Cloud Professional Data Engineer Certification
  • Experience supporting AI/ML data pipelines
  • The base compensation range for this role in the posted location is: 80420 - 106050
  • Cap*** provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws.
  • The base compensation range listed for this position reflects the minimum and maximum target compensation Cap***, in good faith, believes it may pay for the role at the time of this posting.
  • This range may be subject to change as permitted by law.

Responsibilities

  • Data Engineering & Pipeline Development
  • Design, build, and maintain scalable batch and real-time data pipelines using GCP services such as Dataflow, Dataproc, and Pub/Sub
  • Develop and optimize ETL/ELT workflows for structured and unstructured data processing
  • Implement event-driven data processing using Cloud Functions and Pub/Sub
  • Build and manage data ingestion frameworks for streaming and batch data sources
  • Data Storage & Processing
  • Design and optimize data lakes and data warehouses using BigQuery and Cloud Storage
  • Develop efficient data models to support analytics, reporting, and machine learning workloads
  • Optimize performance and cost of data pipelines and queries
  • Development & Automation
  • Develop reusable and scalable solutions using Python
  • Automate workflows and orchestration using Cloud Composer (Airflow)

Degrees

Associate

Industry

AutomotiveEducationEnergyHealthcareInsuranceLogisticsMedia

Company size

EnterpriseSmb