Senior Data Analyst/ Technical Steward

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Job Description

About the role:

Takeda is taking a giant step forward to create a future-ready organization that evolves at the speed of science and technology, to meet the needs of patients by seeking and incorporating novel data & digital capabilities, and agile methodologies. Our aim for Global Manufacturing Supply and Global Quality (GMSGQ) is to create a data-driven, highly automated, and AI-enabled ecosystem that enables a transformation with ambitious strategic business aspirations and value opportunities. Our Data, Digital and Technology teams play an integral role in accelerating this exciting journey.

A Senior Data Analyst/ Technical Steward is working at the interface between the various GMSGQ functions and the data integration team and responsible for developing and maintaining business-centric knowledge and data models which are the backbone for the GMSGQ global data model. The aspiration is to transform the way our teams work with data across all production sites of the Global Manufacturing and Supply/Global Quality organization for the benefit of the patients we serve around the globe.

This role is part of the Data Strategy & Governance team and essential to achieve the GMSGQ DD&T transformation. The Data Strategy & Governance team enables and drives data capabilities and solutions across Takeda. The team works closely with our GMSGQ partners around the globe, serving state-of-the art data solutions to enable decision support, business and manufacturing intelligence and advanced predictive analytics.

• Support GMSGQ units to describe and model their data domains in a processes-centric way

• Streamline data generation, collection and integration

• Ensure that functional knowledge that is existing in the organization is formalized, conserved and available to users to support business decisions

• Facilitate the transformation of Takeda to become a data-driven organization and drive change management activities.

How you will contribute:

• Acts as technical SME for business data domains

• Oversees the creation and refinement of requirements for development teams

• Develops conceptual data and knowledge models and manages business glossaries and taxonomies

• Works hands-on with and directs the data engineering team to create physical data models that capture relevant business dimensions to enable enhanced BI, analytics, and data science

• Supports the development of data products by providing functional knowledge

• Leads small projects to improve the GMS/GQ data lake and data warehouse

• Supports software development lifecycle activities, especially by providing expert input in the development of functional test strategies

• Drive data governance activities like cataloging, taxonomy management, data quality monitoring and issue resolution

Core Elements Related to this role

• Strong analytical and problem-solving skills

• Ability to work in a fast-paced, dynamic environment, and manage multiple priorities and projects simultaneously

• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams

What you bring to Takeda:

• 3 years or more of relevant experience preferably a bachelor’s degree in information science or a comparable field.

• Ability to write, speak and lead in the English language.

• Up-to-date specialized knowledge in data management.

• Hands-on experience in knowledge engineering (taxonomy/ontology creation) and application.

• Profound understanding of data integration and ETL platforms (e.g., Amazon DMS, Databricks, Informatica Cloud, Oracle Golden Gate).

• In-Depth knowledge of SQL and Relational Databases.

• Experience with AWS (S3, EC2, Redshift, EMR, Athena).

• Understanding of Web Services as well as JSON formats.

• Knowledge about semantic web standards and underlying technologies (Triple stores, labelled property graphs).

• Understanding of at least one relevant business domain (supply chain, pharmaceutical manufacturing, quality assurance, quality control).

Preferred:

• Understanding of Data Science workflows, including Machine Learning and / or Deep Learning.

• Experience with NoSQL datastores (MongoDB, Neo4J, DocumentDB, GraphDB).

• Experience in designing JSON/XML standards.

• Additional Languages: PySpark, Python, Javascript.

• Experience in Computer Systems Validation GAMP.

• Experience with data formats including Parquet, ORC or AVRO.

• Experience with Business Intelligence and Tools (Qlik/PowerBI).