EY - GDS Consulting - AI And DATA -AWS Data Engineer - Senior

Overview

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Job Description – Data Products AWS Data Engineer

Objectives and Purpose

• The Senior Data Engineer ingests, builds, and supports large-scale data architectures that serve multiple downstream systems and business users. This individual supports the Data Engineer Leads and partners with Visualization on data quality and troubleshooting needs.
• The Senior Data Engineer will:
• Clean, aggregate, and organize data from disparate sources and transfer it to data warehouses.
• Support development testing and maintenance of data pipelines and platforms, to enable data quality to be utilized within business dashboards and tools.
• Create, maintain, and support the data platform and infrastructure that enables the analytics front-end; this includes the testing, maintenance, construction, and development of architectures such as high-volume, large-scale data processing and databases with proper verification and validation processes.
  

• Strong Clinical and Operational domain knowledge in Pharma (Life Science ) Industry
• Must have 3 to 5 years of experience with Python (or a similar language) and Data Engineering.
• Hands on experience with EMR
• Hands on experience with AWS ( Athena, Redshift)
• Hands on experience working with Snowflake
• Hands on experience with DataIku
• Good to have working exposure to Databricks
• Hands on experience with Dremio
• Expert-level experience in creating/analyzing complex SQL and creating data pipelines, data modeling skills, and frameworks.
• Expert-level experience in creating/analyzing complex SQL and creating data pipelines, data modeling skills, and frameworks.
• Strong technical knowledge and extensive application support experience in systems and applications within clinical development
• Problem-solving, analytical, quality mindset, and strong business acumen
• Ability to translate complex business questions and requirements and develop effective solutions.
• Understanding of clinical data standards
• Excellent analytical skills
• Detail-oriented, demonstrating good interpersonal and leadership skills, a team player.
• Self-motivated, work effectively under pressure.
• Effective verbal and written communication skills
  
  

• Experience: 3-5 years of progressive experience in Data Engineering, Data Warehousing, or a related role.
• Programming: Expertise in Python for data manipulation, scripting, and pipeline development.
• Data Transformation: Strong proficiency with modern SQL and experience with dbt (data build tool) for implementing data transformations and quality checks.
• Big Data Ecosystem: Hands-on experience with PySpark and distributed processing frameworks, specifically on AWS EMR.
• Cloud Data Warehousing: Practical experience working with and optimizing large datasets in cloud data warehouses such as Amazon Redshift and/or Snowflake.
• Cloud Storage: Experience with Amazon S3 for building and managing data lakes.
• DevOps/CI/CD: Familiarity with CI/CD tools like Jenkins and source control systems, specifically Bitbucket (or similar like Git/GitHub/GitLab).
• Methodology: Proven experience working effectively within an Agile - SCRUM development framework.
• Communication: Exceptional written and verbal communication skills with the ability to influence and collaborate across teams.
  
  

• Experience in the Pharmaceutical/Biotech industry, particularly with clinical or regulated data.
• Knowledge of data visualization tools (e.g., Tableau, Power BI).
• Familiarity with containerization technologies (e.g., Docker, Kubernetes).
• Bachelor's or master’s degree in computer science, Engineering, or a related field.
  
  

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