Data Engineering Engineer V

Takeda Pharmaceuticals International AG; Chihuahua; Presencial; MXN 1,298,000 - 1,671,000; Jornada completa

Descripción de la vacante

A global healthcare company is seeking a Data Engineering Engineer V in Chihuahua, Mexico. This role involves building high-quality data pipelines and collaborating in a multidisciplinary Agile team. Responsibilities include designing data architecture, defining data requirements, and mentoring other data professionals. Candidates should be proficient in SQL, data architecture, and agile methodologies, with experience in distributed technologies like Spark and cloud deployment. This position offers an opportunity to drive data-driven decision-making and analytic capabilities.

Formación

• Expert in designing and maintaining scalable data architectures.
• Proficient in SQL and other data manipulation languages.
• Skilled in DevOps practices and continuous integration.
• Experienced in software development methodologies.
• Knowledgeable in data structures and algorithms.
• Familiar with distributed data technologies like Spark and Hadoop.
• Efficient in system integration across platforms.
• Proficient in programming languages such as Python, Scala, Java, and C++.
• Experienced in SQL database management and performance tuning.
• Skilled in cloud platform deployment and tools like Kubernetes.
• Advanced in PL/SQL and MongoDB database programming.

Responsabilidades

• Design, develop, optimise, and maintain data architecture and pipelines.
• Define data requirements and validate data using various tools.
• Support Data Scientists in data sourcing and preparation.
• Lead the evaluation and implementation of emerging tools for data processing.
• Develop communication and education plans on analytic data capabilities.
• Partner with business analysts to develop technical architectures.
• Mentor and coach data professionals on standards and practices.

Conocimientos

Data architecture design

SQL proficiency

DevOps practices

Software development

Data structures and algorithms

Distributed data technologies (Spark, Hadoop)

System integration

Python programming

SQL database management

Cloud platform deployment (Kubernetes)

PL/SQL and MongoDB

Descripción del empleo

Please be aware of identity thieves actively posing as Takeda employees or recruiters posting Takeda‑branded jobs online to steal personal information from job seekers. We care about your privacy and candidate experience. Follow instructions to spot fraudulent messages.

At Takeda, we are guided by our purpose of creating better health for people and a brighter future for the world. Every corporate function plays a role in making sure we — as a Takeda team — can discover and deliver life‑transforming treatments, guided by our commitment to patients, our people and the planet.

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, optimise, 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 visualise 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 optimise 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.
• Proficient in programming languages such as Python, Scala, Java, and C++, applying them effectively in data engineering tasks.
• Experienced in SQL database management, performance tuning, and complex query handling.
• Skilled in cloud platform deployment and tools like Kubernetes, optimising 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 optimisation.