Data Scientist – (Research Development & Engineering area)

Kimberly Clark; Argentina; Presencial; ARS 59.940.000 - 86.581.000; Jornada completa

Descripción de la vacante

A leading consumer products company is seeking an experienced Data Scientist to join their team in Buenos Aires, Argentina. The role involves designing and implementing analytics solutions to support decision-making processes, maintaining data quality, and collaborating with various teams. Ideal candidates will have a Bachelor's degree and over 5 years of experience in data engineering with strong proficiency in SQL and analytics tools.

Formación

• 5+ years of experience in data engineering, designing, developing, and building solutions.
• Strong knowledge with data collection, analyses, cleaning to build reports for stakeholders.
• Fluency in English required.

Responsabilidades

• Design and develop ETL and ELT pipelines to process data.
• Build models that are interpretable and scalable.
• Mentor junior engineers on data engineering techniques.

Conocimientos

SQL

API

Power Query

Microsoft Power BI

Data Factory

Data Bricks

Educación

Bachelor's degree

Herramientas

SQL Server

Databricks

Snowflake

HANA

Teradata

Descripción del empleo

Overview

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.

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 environment.
• Collaborate with platform teams to design and build automated processes for pipeline construction, testing, and code migration.

About Us

Huggies. Kleenex. Cottonelle. Scott. Kotex. Poise. Depend. Kimberly-Clark Professional. You already know our legendary brands—and so does the rest of the world. In fact, millions of people use Kimberly-Clark products every day. We know these amazing Kimberly-Clark products wouldn’t exist without talented professionals, like you.

At Kimberly-Clark, you’ll be part of the best team committed to driving innovation, growth and impact. We’re founded on more than 150 years of market leadership, and we’re always looking for new and better ways to perform – so there’s your open door of opportunity. It’s all here for you at Kimberly-Clark.

About You

You perform at the highest level possible, and you appreciate a performance culture fueled by authentic caring. You want to be part of a company actively dedicated to sustainability, inclusion, wellbeing, and career development.

You love what you do, especially when the work you do makes a difference. At Kimberly-Clark, we’re constantly exploring new ideas on how, when, and where we can best achieve results. When you join our team, you’ll experience Flex That Works: flexible work arrangements that empower you to have purposeful time in the office and partner with your leader to make flexibility work for both you and the business.

Who you are?

Mandatory:

• Bachelor’s degree required.
• Fluency in English
• 5+ years of experience in data engineering and designing, developing, and building solutions on platforms like.
• Strong Proficiency with SQL, API, Power Query and Microsoft Power BI.
• Experience with Data Factory and Data Bricks.
• Strong knowledge with data collection, analyses, cleaning to build reports for stakeholders.

Nice to have:

• Experience with Python.
• Exposure to SQL Server, and Databricks, HANA, Snowflake and Teradata.
• Proven track record in building and maintaining data pipelines, data warehousing, and data modeling.
• Strong communication skills, both oral and written, with the ability to convey complex technical concepts to non-technical stakeholders.
• Ability to work independently and collaboratively in a team environment.
• Familiarity with DevOps tools and practices for continuous integration and deployment.

Travel: This position may require occasional travel (approximately 0-10% of work time).

To Be Considered

Click the Apply button and complete the online application process. A member of our recruiting team will review your application and follow up if you seem like a great fit for this role.

In the meantime, please check out the careers website.

And finally, the fine print….

For Kimberly-Clark to grow and prosper, we must be an inclusive organization that applies the diverse experiences and passions of its team members to brands that make life better for people all around the world. We actively seek to build a workforce that reflects the experiences of our consumers. When you bring your original thinking to Kimberly-Clark, you fuel the continued success of our enterprise. We are a committed equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation, gender identity, age, pregnancy, genetic information, citizenship status, or any other characteristic protected by law.

The statements above are intended to describe the general nature and level of work performed by employees assigned to this classification. Statements are not intended to be construed as an exhaustive list of all duties, responsibilities and skills required for this position.

Employment is subject to verification of pre-screening tests, which may include drug screening, background check, and DMV check.

#LI-hybrid

Primary Location Brazil -Sao Paulo

Additional Locations Argentina-Buenos Aires

Worker Type Employee

Worker Sub-Type Regular

Time Type Full time