Data Engineer - Life Sciences Sector - Manager - Consulting - Location OPEN

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. Join us and build an exceptional experience for yourself, and a better working world for all.   The exceptional EY experience. It's yours to build.   EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.  

Consulting Manager, Data Engineering, Life Science Sector: This position can be anywhere in the country.

 

The Opportunity

Our Artificial Intelligence and Data team is dedicated to implementing cutting-edge technology and techniques to deliver innovative solutions to our clients in the Life Science sector. As a Manager, you will work closely with clients and interdisciplinary teams within EY to provide comprehensive solutions to complex challenges, some of which are unprecedented. Your role will be dynamic, involving continuous research and development, and will require a passion for continuous learning. You will be expected to stay ahead of industry trends and influence new methodologies to position solutions effectively for our clients. This role offers significant client interaction, a fast-paced work environment, and the opportunity to shape your career path based on your unique skills and ambitions.

 

Your Key Responsibilities

In this role, you will collaborate with a diverse range of clients to deploy the latest data engineering technologies and methodologies. You will design and build robust, scalable solutions for Life Science clients that integrate and enrich data from various sources across a broad technology landscape. Your goal will be to help our clients make sense of complex data science, analytics, and software engineering challenges. You will provide guidance and perform technical development tasks to ensure data engineering solutions are properly engineered and maintained to support ongoing business needs.

 

Joining our dynamic team, you will engage with scientists and engineers who are passionate about solving computational problems for our clients. Our team members often have advanced academic degrees or equivalent industry experience and excel in creative thinking, efficient application development, and collaboration in both solution ideation and the pursuit of new opportunities.

 

Skills and Attributes for Success

This role requires delivering technology swiftly, innovating at scale, and placing humans at the center of solutions. You will provide technical guidance and share knowledge with team members from various backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding emerging technology. You should demonstrate technical capabilities, professional knowledge, and a commitment to continuous learning about EY's service lines, actively seeking ways to apply your knowledge and services.

 

To Qualify for the Role You Must Have

• Bachelor’s degree and 6-10 years of full-time working experience in Data Engineering, Big Data, and related fields.
• 2-4 years of experience directly managing technical teams.
• At least 2 years working in the Life Science domain, developing data solutions for challenges in drug discovery, clinical trials, or patient data management.
• Strong skills in Python and other data manipulation languages.
• Experience with data engineering models and frameworks, including data ingestion, transformation, and insight generation.
• Extensive experience with DevOps tools like GIT, Azure DevOps, and Agile tools such as Jira for developing and deploying data solutions.
• A solid understanding of data engineering workflows, including data collection, transformation, and analysis.
• Experience with data engineering methods and platforms such as Apache Airflow or similar.
• Experience with CI/CD and test-driven development.
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