Merck KGaA

Head of Data Engineering

Posted On

Oct. 21, 2024

Location

Bangalore, Karnataka

Experience Level

E - Professional (10+ years)

Job Type

full-time or part-time possible

Apply By

Dec. 3, 2024

Job Description

Job Description:Join us to contribute to the org's enterprise priority of driving innovation through data & digital. In R&D, the promise of bringing more medicines to more patients faster is closely linked with the ability to maximize the use of our data for improved decision making using data analytics & AI. For this, having high-quality data readily available in a well-structured manner is crucial. In your role, you will be leading a team of highly skilled data engineers. Together with your team, you will build efficient, harmonized and stable data pipelines that ensure the data is where it needs to be, in the right form and updated in the right cadence. In this way, you will contribute to the creation of central data repositories as well as specific use cases. Key Responsibilities:Lead the design and development of data engineering solutions that enable actionable insights for our business stakeholders.Manage and mentor a team of data engineers, fostering a culture of innovation and excellence.Maximize the use of our modern Data & AI ecosystem built on AWS, Informatica, Oracle and Snowflake.Ensure top quality data is available for all stakeholders by adopting fast-paced, scalable, and continuously evolving data systems and processes.Foster a culture of engineering excellence, diversity and inclusion that allows everyone to contribute to the team’s success. Qualifications, Experience & Skills:Bachelor’s or Master’s degree in Computer Science or a related field.At least 10 years of professional experience in data engineering, preferably within the Healthcare sector.Experience in leading data engineering teams, driving outcomes and mentoring junior colleagues. Substantial experience in delivering data pipelines especially using Informatica (ideally including IICS), AWS (focusing on Glue, Lambda and DMS) as well as building data repositories using Oracle and Snowflake. Strong knowledge of SQL and ideally Python and PySpark. Strong drive to optimize our data engineering practices, embracing the opportunities offered by our technological setup. Excellent English communication skills, with the ability to engage effectively with both business-facing teams, product owners and technical developers.

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