Senior Data Engineer

hace 7 días


Cuajimalpa, México Takeda Pharmaceutical A tiempo completo

**The Future Begins Here**
At Takeda, we are leading digital evolution and global transformation. By building innovative solutions and futureready capabilities, we are meeting the need of patients, our people, and the planet.

Mexico City has been selected to be home to Takeda’s recently launched Innovation Capability Center thanks to its international recognition in qualified and experienced talent in the data,
digital and technology fields. We invite you to join our digital transformation journey.

In this role, you will have the opportunity to boost your skills and become the heart of an innovative engine that is contributing to global impact and improvement.

**At Takeda’s ICC we Unite in Diversity**
Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team.

**RESPONSIBILITIES**:
The Data Engineering Engineer V collaborates with a multidisciplinary Agile team to build high-quality data pipelines that drive analytic solutions. This role focuses on integrating and managing data to generate insights, enabling advanced data-driven decision-making capabilities.

How you will contribute:

- Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals
- Define data requirements, gather and mine large-scale structured and unstructured data, and validate data using various data tools in the Big Data Environment
- Support Data Scientists in data sourcing and preparation to visualize data and synthesize insights of commercial value
- Lead the evaluation, implementation, and deployment of emerging tools and processes for analytic data engineering to improve productivity
- Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes
- Partner with business analysts and solutions architects to develop technical architectures for strategic enterprise projects and initiatives
- Mentor and coach other data and analytic professionals on data standards and practices

**SKILLS AND QUALIFICATIONS**:

- Expert in designing and maintaining scalable data architectures, capable of handling complex data systems.
- Proficient in SQL and other data manipulation languages, with a strong ability to optimize and troubleshoot queries.
- Skilled in DevOps practices and continuous integration to enhance workflow efficiencies.
- Experienced in software development methodologies, contributing to both project and operational goals.
- Knowledgeable in data structures and algorithms, enhancing data processing and storage solutions.
- Familiar with distributed data technologies like Spark and Hadoop, capable of managing large-scale data operations.
- Efficient in system integration, ensuring seamless data flow and connectivity across platforms.
- Experienced in SQL database management, performance tuning, and complex query handling.
- Skilled in cloud platform deployment and tools like Kubernetes, optimizing cloud-based data solutions.
- Capable of performing advanced troubleshooting and guiding others through complex problem-solving processes.
- Advanced in PL/SQL and MongoDB, providing guidance and advice on complex database programming and optimization.

As an experienced professional, you specialize in solving various complex problems, sometimes referring to established precedents and policies. Your work involves analyzing diverse data and selecting appropriate methods for solutions, while networking with senior professionals in your field. You possess a complete understanding of principles, concepts, and industry practices, exerting some influence on organizational objectives. You often work independently under general direction, occasionally leading small project teams, and may represent the organization in contractual or project matters, interacting with senior internal and external personnel. You might also participate in training junior staff.

**Locations**: MEX - Santa Fe

**Worker Type**: Employee

**Worker Sub-Type**: Regular

**Time Type**: Full time


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