Principal Data Engineer

**About the role**:
The Data Engineering Senior Engineer collaborates with a multidisciplinary Agile team to build high-quality data pipelines that drive analytic solutions. This role focuses on generating insights from connected data, enabling advanced data-driven decision-making capabilities.

**How you will contribute**:

- Contribute to the data engineering of existing and new IT Systems to design, to analyze and implement complex manufacturing data driven solutions, with an impact on the daily operation of our manufacturing processes and facilities.
- Enable data analytics (process trending, process modelling, real-time analytics, and predictive analytics) in a GxP environment from an IT perspective for all GMS sites
- Develop and maintain scalable data pipelines using AWS native technologies and Databricks to support increasing data sources, volumes, and complexity.
- Drive identification of technical issues, problem-solving and escalating issues appropriately.
- Ensure Digital Products and Platforms are built efficiently, scalable and on state-of-the-art technology.
- Provides guidance to business partners and solves complex technical changes and implementations.
- Follow company and departmental policies, procedures and ensure documentation according to the Takeda Quality Management Systems (QMS), Software Development Life Cycle and Project Life Cycle standards.
- Collaborate with analytics and business teams to improve data models that enhance business intelligence tools and dashboards, fostering data-driven decision-making across the organization.

**What you bring to Takeda**:**
- Bachelor’s Degree in Computer Science or in a Technical/Natural Science (with focus on IT) or equivalent,
- 7 years of experience in data engineering, or a related field,
- In-Depth knowledge of SQL and Relational Databases,
- Strong expertise in data modeling, and modern database technologies (Databricks, Oracle, MongoDB),
- Basic understanding of batch-based manufacturing processes,
- Understanding of Shop-Floor systems (MES, ERP, LIMS, Historian, etc.),
- Understanding of Agile/SCRUM methodologies,
- Understanding of good engineering practices (DevSecOps, source-code versioning),
- Excellent written and verbal communication skills, with the ability to collaborate effectively with cross-functional teams,
- Fluency in English.

**Nice to Have**
- Experience with working in a highly regulated industry (e.g. pharmaceutical - or chemical industry)
- Experience with AWS (S3, EC2, Terraform),
- Experience in Computer Systems Validation GAMP,
- Understanding of Data Science workflows, including Machine Learning and / or Deep Learning.

**_ What Taked_**_ _**_a can offer you:_**
- Competitive salary + Annual performance bonus
- Monthly food and meal vouchers
- Flexible work arrangements
- Comprehensive health insurance plans: life, medical, dental, and vision
- Diversity, equity, and inclusion programs
- Among other benefits

**More about us**:
At Takeda, we are transforming patient care through the development of novel specialty pharmaceuticals and best in class patient support programs. Takeda is a patient-focused company that will inspire and empower you to grow through life-changing work.

Certified as a Global Top Employer, Takeda offers stimulating careers, encourages innovation, and strives for excellence in everything we do. We foster an inclusive, collaborative workplace, in which our teams are united by an unwavering commitment to deliver Better Health and a Brighter Future to people around the world.

**Empowering our people to shine**:
Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, or any other characteristic protected by law

**Locations**: MEX - Santa Fe

**Worker Type**: Employee

**Worker Sub-Type**: Regular

**Time Type**: Full time