Data Engineer

In the Center of Excellence Pricing and Analytics organization our mission is to deliver impact by building machine learning products to optimize pricing, sales, marketing and inventory investments and provide guidance to HP's commercial sales organizations. The organization consists of a diverse global team of economists, statisticians, data scientists, data engineers, software engineers, DevOps, and MLOps engineers, who are pushing the innovation frontier to bring new insights to our business.

We are looking for a Data Engineer to join our data engineering team. If you are passionate about solving problems and making improvements through data and technology, we are eager to talk to you. The ideal candidate has both a willingness and desire to work in a dynamic environment, is able to apply Agile methodologies in day-to-day activities, and is a self-motivated developer who also enjoys working in a team environment. Our people have a creative, innovative, fun, and collaborative attitude, and are dedicated to creating new and valuable solutions for HP.

Job Responsibilites:

• Analyze and model data

• Develop, debug and optimize data pipelines and continuesly raise their quality

• Technical ownership and be an SME of an area of our data assets

• Build strong documentation and high quality code

• Work and collaborate with stakeholders and a global team on high quality deliverables

Job Requirements:

• Typically 2+ years of experience in software or data engineering.

• Extensive experience in data modeling, data integration and processing of structured and unstructured data.

• Proficient in one or more programming languages (Python preferred).

• SQL proficiency (experience with NoSQL – advantage).

• Experienced with Apache Spark

• Excellent communication skills; mastery in English and local language.

• Ability to effectively communicate product architectures, design and change proposals.

Nice to have:

• Worked in Databricks / Databricks certified

• Pandas

• Familiar with best practices of the data and software engineering lifecycle and/or best practices of the above platforms and tools.

• Familiar with scrum, JIRA and GitHub

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