Summary: The Data Engineering Engineer IV collaborates with an Agile team to build high-quality data pipelines and drive analytic solutions, focusing on generating insights and enabling advanced data-driven decision-making. Highlights: 1. Design, develop, optimize, and maintain data architecture and pipelines 2. Lead evaluation and deployment of emerging tools for analytic data engineering 3. Mentor and coach other data and analytic professionals on data standards By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. **Job Description** ------------------- About the role: The Data Engineering Engineer IV 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: * 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 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 * Partner with business analysts and solutions architects to develop technical architectures for strategic enterprise projects and initiatives * Implement statistical data quality procedures on new data sources by applying rigorous iterative data analytics * Advise, consult, mentor, and coach other data and analytic professionals on data standards and practices Skills and qualifications: * Applies advanced techniques in data engineering and modeling, capable of leading initiatives and mentoring others. * 3\+ years of experience. * Proficient in DevOps practices and continuous integration, enhancing operational efficiencies and deployment strategies. * Demonstrates expertise in software development methodologies and data structures, optimizing algorithms for complex data operations. * Skilled in distributed data technologies like Spark and Hadoop, improving large\-scale data processing and analytics. * Experienced in system integration, ensuring seamless data flow and functionality across various platforms. * Proficient in programming languages such as Python, Scala, Java, and C\+\+, tailored for scalable data engineering solutions. * Advanced knowledge of SQL, executing complex queries and managing databases effectively. * Expertise in deploying and managing applications on cloud platforms using tools like Kubernetes, enhancing scalability and reliability. * Strong analytical skills, capable of transforming data into actionable insights that drive decision making. * Leadership capabilities, able to guide and inspire junior engineers, fostering a collaborative and innovative work environment. As a senior professional, you're adept at solving a range of moderate scope and complexity problems, occasionally referring to policies and practices for guidance. Your work involves analyzing situations and data, exercising judgment within established procedures, and fostering productive relationships internally and externally. You possess solid knowledge of industry practices and contribute to departmental projects and goals, often engaging in frequent internal and external interactions. You may occasionally lead small project teams and provide informal guidance to junior staff, all while working with minimal guidance yourself.**Locations** ------------- MEX \- Santa Fe**Worker Type** --------------- Employee**Worker Sub\-Type** -------------------- Regular**Time Type** ------------- Full time