Data Engineer, Advanced

Remote Work: Yes

Overview:

At Zebra, we are a community of innovators who come together to create new ways of working to make everyday life better. United by curiosity and care, we develop dynamic solutions that anticipate our customer’s and partner’s needs and solve their challenges.

Being a part of Zebra Nation means being seen, heard, valued, and respected. Drawing from our diverse perspectives, we collaborate to deliver on our purpose. Here you are a part of a team pushing boundaries to redefine the work of tomorrow for organizations, their employees, and those they serve.

You have opportunities to learn and lead at a forward-thinking company, defining your path to a fulfilling career while channeling your skills toward causes that you care about – locally and globally. We’ve only begun reimaging the future – for our people, our customers, and the world.

Let’s create tomorrow together.

Role:

A Data Engineer will be responsible for understanding the client's technical requirements, designing and building data pipelines to support these requirements. In this role, the Data Engineer will also oversee other Engineers' development. This role requires strong verbal and written communication skills and the ability to effectively communicate with the client and internal team. A strong understanding of databases, SQL, cloud technologies, and modern data integration and orchestration tools like Azure Data Factory (ADF), Informatica, and Airflow are required to succeed in this role.

Responsibilities:

1. Play a critical role in the design and implementation of data platforms for AI products.
2. Develop productized and parameterized data pipelines that feed AI products leveraging GPUs and CPUs.
3. Develop efficient data transformation code in Spark (in Python and Scala) and Dask.
4. Build workflows to automate data pipelines using Python and Argo.
5. Develop data validation tests to assess the quality of the input data.
6. Conduct performance testing and profiling of the code using a variety of tools and techniques.
7. Guide Data Engineers in delivery teams to follow best practices in deploying data pipeline workflows.
8. Lead design sessions to develop ETL logic that meets business and product requirements.
9. Implement data pipelines that meet the design and are efficient, scalable, and maintainable.
10. Provide technical guidance and meet best practices during data pipeline development.
11. Work with clients to understand and document their data, technology, and how it would integrate with Antuit's cloud solutions.
12. Act as a technical escalation lead for customer and development team issues.
13. Build data pipeline frameworks to automate high-volume and real-time data delivery for our data hub.
14. Operationalize scalable data pipelines to support data science and advanced analytics.
15. Optimize customer data science workloads and manage cloud services costs/utilization.
16. Develop sustainable data-driven solutions with current new generation data technologies to drive our business and technology strategies.

Qualifications:

Required Qualifications:

• Bachelor's, Master's, or Ph.D. Degree in Computer Science or Engineering; 7-10 years experience in the Data Engineering field.
• Strong understanding of data models that feed advanced AI-driven applications.
• Fluent level of English (written and verbal) as well as local language as applicable.

Preferred Qualifications:

• At least 3 years of experience with Azure Data Factory (ADF), Informatica, and similar.
• At least 1 year of Spark experience (preferably PySpark).
• Experience with relational databases, SQL, and Python is preferred.
• Experience working with Retail, Consumer Goods, and Manufacturing data models is a plus.