Data Engineer - EMEA Data & Analytics

Data Engineer - EMEA Data & Analytics

Lo que hacemos

En Kenvue, nos damos cuenta del extraordinario poder del cuidado diario. Sobre la base de más de un siglo de herencia y arraigados en la ciencia, somos el hogar de marcas icónicas, incluidas NEUTROGENA®, AVEENO,® TYLENOL,® LISTERINE,® JOHNSON'S® y BAND-AID® que ya conoces y amas. La ciencia es nuestra pasión; El cuidado es nuestro talento.

Quiénes somos

Nuestro equipo global está formado por ~ 22.000 personas brillantes con una cultura laboral en la que cada voz importa y cada contribución es apreciada. Nos apasionan las ideas, innovación y comprometidos con la entrega de los mejores productos a nuestros clientes. Con experiencia y empatía, ser un Kenvuer significa tener el poder de impactar a millones de personas todos los días. Ponemos a las personas en primer lugar, nos preocupamos ferozmente, nos ganamos la confianza de la ciencia y resolvemos con coraje, ¡y tenemos oportunidades brillantes esperándote! Únase a nosotros para dar forma a nuestro futuro y al suyo. Para obtener más información, haga clic en aquí.

Role reports to:

Manager Data & Analytics EMEA

Ubicación:

Asia Pacific, India, Karnataka, Bangalore

Lugar de trabajo:

Híbrido

What will you

Job Title: Data Engineer - EMEA Data & Analytics

Location: Bangalore

Company: Kenvue

Position Summary: We are seeking a skilled Data Engineer to join our dynamic EMEA data and analytics team. The ideal candidate will have a strong background in data engineering, with hands-on experience in utilizing the Kenvue Data Platform, which includes Snowflake/Databricks, Apache Airflow, dbt/PySpark, Streamlit, GitHub and Python. As a Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines that support our analytics and reporting needs.

Key Responsibilities:

• Data Pipeline Development: Design, implement, and maintain robust data pipelines using Apache Airflow, ensuring data is ingested, transformed, and made available for analytics and reporting.

• Data Warehousing: Utilize Snowflake/Databricks for data storage, management, and optimization, ensuring high performance and reliability of data access.

• Data Transformation: Employ dbt (data build tool)/PySpark to develop and manage the data transformation workflow, ensuring data quality, consistency, and documentation.

• Data Visualization: Collaborate with data visualization developers (PowerBI) and stakeholders to create interactive dashboards and data applications using Streamlit, providing insights and supporting decision-making processes.

• Programming & Scripting: Write efficient and scalable code in Python to automate data processes, perform data cleansing, and manage ETL workflows.

• Collaboration: Work closely with cross-functional teams including data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights.

• Monitoring & Maintenance: Implement monitoring solutions to ensure data quality, pipeline health, troubleshoot issues, and optimize performance.

• Version Control: Utilise GitHub to follow best version control practices.

• Documentation: Maintain comprehensive documentation of data workflows, methodologies, and best practices to ensure knowledge sharing within the team.

• Support and Maintenance: Ability to take over the support/maintenance of existing solutions built on the Kenvue Data Platform.

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.

• 3+ years of experience in data engineering or a related role.

• Hands-on experience with Snowflake/Databricks, Apache Airflow, dbt, Streamlit, GitHub and Python.

• Strong understanding of ETL/ELT processes, data modeling, and data warehousing concepts.

• Proficiency in SQL and experience with data querying and analysis.

• Familiarity with data visualization tools and techniques (PowerBI)

• Excellent problem-solving skills and attention to detail.

• Strong communication and collaboration skills, with the ability to work effectively in a team-oriented environment.

Preferred Qualifications:

• Knowledge of data governance and data security practices.

• Knowledge of data observability best practices.

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