Data Scientist – (Research Development & Engineering area)

Data Scientist – (Research Development & Engineering area)

Job Description

You’re not the person who will settle for just any role.

Neither are we.

Because we’re out to create Better Care for a Better World, and that takes a certain kind of person and teams who care about making a difference.

Here, you’ll bring your professional expertise, talent, and drive to building and managing our portfolio of iconic, ground-breaking brands.

In this role, you’ll help us deliver better care for billions of people around the world.

It starts with YOU. 

In this role, you will:

Kimberly-Clark is seeking a motivated and skilled data scientist to join our dynamic team.

The ideal candidate will play a pivotal role in designing and building analytics solutions to facilitate informed decision-making.

The developer will work closely with various R&D and DTS technology teams to design and implement scalable data pipelines, design analytics within R&D solutions, and ensure the accuracy and availability of data for analytics and reporting.

Primary focus of the position is to design, develop, and maintain analytics solutions.

Customers: Research & Development, Global Growth, and Quality Assurance.

Key Responsibilities:

Data Collection and Integration:


* Collaborate with engineering and architecture teams to identify, collect, and harmonize data from various sources.


* Design and develop ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) pipelines to process and curate data sets using technologies such as SQL Server, Azure Data Factory and Databricks.

Data Modeling and Warehousing:


* Develop and maintain data models and data warehouses using platforms like SQL Server, Azure Data Factory, Snowflake, and Databricks.


* Apply metadata-driven frameworks to ensure scalable data ingestion and processing.

Data Quality and Standards:


* Implement data quality checks and validation frameworks to maintain high data standards.


* Build and maintain data development standards and principles, providing guidance and project-specific recommendations.

Analytics and Reporting:


* Build models that are interpretable, scalable, and meet business needs.


* Develop visualizations to demonstrate the results of data models to stakeholders and leadership, leveraging Microsoft Azure technologies.


* Test and validate analytics solutions to ensure data integrity and actual results meet expected results.

Collaboration and Mentorship:


* Work with principal architect, product owners, solution engineers, business customers, and other key stakeholders to translate requirements into technical designs.


* Mentor junior engineers and team members on data engineering techniques and best practices.


* Train and build the talent of business users to maximize the return on investment of the analytics solutions.

Agile and DevOps Practices:


* Use Agile methodologies and tools to deliver products in a fast-paced envi...