Cloud Data Engineering Lead

5 days ago


New York, New York, United States HR Recruiting Services Full time

**Job Title:** Cloud Data Engineering Lead

**Job Type:** Full-time

**Location:** Remote (USA)

**Salary:** $150,000 - $200,000 per year

We are seeking an experienced Cloud Data Engineering Lead to join our team at HR Recruiting Services. The ideal candidate will have a strong background in data engineering and cloud computing, with a proven track record of designing and implementing scalable data pipelines and ETL processes.

**Job Description:

Key Responsibilities:
  • Design and implement efficient and reliable data pipelines and ETL processes using Python and SQL
  • Manage and work with our database managed service provider (MSP) to manage and monitor our evolving database requirements
  • Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality data solutions
  • Implement and manage data storage solutions in cloud environments (AWS, Azure, Google Cloud)
  • Ensure data quality and integrity through rigorous testing and validation
  • Continuously evaluate and integrate new technologies and tools to improve data processing capabilities
  • Manage distributed scheduled tasks on individual servers to a centralized ruleset
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field from a top-tier university
  • 4-5 years of relevant professional experience in data engineering
  • Strong programming skills in SQL and Python
  • Proficiency in database administration
  • Proven experience migrating on-prem data and associated processes to cloud platforms (AWS, Azure, Google Cloud)
  • Demonstrated ability to design and implement efficient and reliable data pipelines and ETL processes

**Benefits:

  • Competitive salary range: $150,000 - $200,000 per year
  • Opportunity to work with a leading company in the industry
  • Chance to develop your skills and expertise in cloud data engineering


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