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Lead Data Engineer

Python.Data, Pandas, Python, SQL
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Sorry, this position is no longer available

We are looking for a skilled remote Lead Data Engineer to join our team and help build data pipelines for our projects. You will be responsible for managing and developing data pipelines, as well as overseeing a team of Data Engineers. This role requires extensive knowledge of Python and SQL, with a focus on data manipulation using Pandas.

Responsibilities
  • Collaborate with other teams, including Data Scientists and Data Analysts, to understand business requirements and build data pipelines accordingly
  • Design and develop scalable data pipelines using Python and SQL
  • Oversee a team of Data Engineers, providing guidance and support as needed
  • Ensure the quality of data pipelines, including data accuracy, reliability, and efficiency
  • Create and maintain technical documentation for data pipelines and related systems
  • Implement and maintain security and compliance measures for data pipelines
  • Stay up-to-date with the latest trends and technologies in data engineering
Requirements
  • Minimum of 5 years of experience in building data pipelines, with direct experience in using SQL
  • Proficient in Python, with specific experience in data manipulation using Pandas
  • Strong leadership skills, with experience in leading and managing a team (1+ year experience)
  • Excellent communication skills, with the ability to collaborate with other teams effectively
  • Fluent in English, with an Upper-Intermediate level of proficiency
Benefits
  • International projects with top brands
  • Work with global teams of highly skilled, diverse peers
  • Healthcare benefits
  • Employee financial programs
  • Paid time off and sick leave
  • Upskilling, reskilling and certification courses
  • Unlimited access to the LinkedIn Learning library and 22,000+ courses
  • Global career opportunities
  • Volunteer and community involvement opportunities
  • EPAM Employee Groups
  • Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn

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