Cloud Platform Engineer

Job Description

At The Estée Lauder Companies (ELC), we believe that technology will power the future of beauty. Across more than 25 globally recognized brands sold in over 150 countries and territories, we use technology to reinvent and redefine how consumers worldwide explore and express their individual beauty. Infused throughout our organization is a passion for creativity and innovation and a desire to push the boundaries and invent the unexpected.

Our Digital Technology Centers are made up of talented individuals who exemplify ELC’s heritage of high-performance, innovation, and family values. We’re looking for creators, leaders, and visionaries with the passion and imagination to shape the next generation of beauty products and experiences. We’re hiring technologists at all levels.

The Data Engineer will join our data engineering capability in ELC’s Eastern European Center, located in Bucharest. Helping ELC to become a data-driven organization, the role is responsible to contribute to the development of reusable data products and solutions that drive business outcomes.

Working within a virtual global team, the profile will have the opportunity to work on analytical projects across the entire enterprise. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our global team on data initiatives and will ensure consistency and adherence to the standards and guidelines of the platforms.

Must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our data architecture to support our next generation of products and data initiatives.

Key Activities

• Transform data with business logic according to functional requirements
• Optimize pyspark code for Databricks
• Design pipelines and integrate code into orchestration framework
• Develop reusable libraries for reuse of common transformation patterns
• Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs.
• Create data tools for analytics and data scientist team members to assist them in building and optimizing our analytical solutions
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, suggest improvements to infrastructure for greater scalability, etc.

Mandatory:

• Python, Pyspark highly desired
• Familiarity with Cloud Service Providers; Azure highly desired.
• Experience with coding in distributed computing environments. Databricks highly desired.
• Hands-on experience with data platforms for Analytics and Reporting.
• Experience performing root cause analysis on internal and external data and processes

Nice to Have:

• Spark Structured Streaming
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• Experience supporting and working with cross-functional teams in a dynamic international environment.

Relevant Experience:

• Data/Analytics Project experience involving SAP data
• Data/Analytics Project experience in CPG or Retail; Beauty industry a plus.
• Project experience that demonstrates strong analytic skills to understand business problems and initiative to solve problem statements with insights derived from data