Ernst & Young Advisory Services Sdn Bhd
EY - GDS Consulting - AI and DATA - Azure DBX - Senior
Ernst & Young Advisory Services Sdn Bhd, Lima, Ohio, United States
EY - GDS Consulting - AI and DATA - Azure DBX - Senior
Location: Kolkata Other locations: Primary Location Only Date: Sep 20, 2025 Requisition ID: 1635490 At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. 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: Bachelor's 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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Location: Kolkata Other locations: Primary Location Only Date: Sep 20, 2025 Requisition ID: 1635490 At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. 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: Bachelor's 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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