EY - GDS Consulting - AI And DATA - Azure DBX - Senior

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EY GDS – Data and Analytics (D&A) – Azure Data Engineer - Senior

Job Summary:

We are seeking a skilled Data Engineer with expertise in Databricks and Python scripting to enhance our ETL (Extract, Transform, Load) processes. The ideal candidate will have a proven track record of developing and optimizing data pipelines, implementing data solutions, and contributing to the overall data architecture.

Key Responsibilities:

• Design, build, and maintain scalable and efficient data pipelines using Databricks and Python.
• Develop ETL processes that ingest and transform data from various sources into a structured and usable format.
• Collaborate with cross-functional teams to gather requirements and deliver data engineering solutions that support business objectives.
• Write and optimize Python scripts for data extraction, transformation, and loading tasks.
• Ensure data quality and integrity by implementing best practices and standards for data engineering.
• Monitor and troubleshoot ETL processes, performing root cause analysis and implementing fixes to improve performance and reliability.
• Document data engineering processes, creating clear and concise technical documentation for data pipelines and architectures.
• Stay current with industry trends and advancements in data engineering technologies and methodologies.
  
  

Qualifications:

• Bachelors degree in Computer Science, Information Technology, or a related field.
• Minimum of 3-5 years of experience in data engineering, with a focus on Databricks and Python scripting for ETL implementation.
• Strong understanding of data warehousing concepts and experience with SQL and NoSQL databases.
• Proficiency in Python and familiarity with data engineering libraries and frameworks.
• Experience with cloud platforms (e.g., AWS, Azure) and big data technologies is a plus.
• Excellent problem-solving skills and attention to detail.
• Ability to work independently and as part of a collaborative team.
  
  

Working Conditions:

• Innovative and dynamic work environment with a strong emphasis on delivering high-quality data solutions.
• Opportunity to work with a diverse team of data professionals and contribute to impactful projects.
  
  

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