Principal Data Engineer

We're looking for a Principal/Staff Data Engineer to join our client's team. 

Our client is a trusted IT services company providing high-quality engineering and technology solutions to global clients.

About the Client

A leading manufacturing company known for innovation and breakthrough products. Their data team powers critical business decisions across commercial, operations, and product development.

Your Role on the Team
As a Principal Data Engineer, you will be a senior technical leader who drives, architects, and delivers innovative data products that enable the company to move with speed, agility, and urgency. 

Responsibilities

• Collaborate directly with Data Architects and business partners to design, enhance, and evolve enterprise-wide data architecture and platform capabilities.
• Translate architectural strategies into technical execution, influencing implementation details, system design, and delivery approach across teams.
• Design, code, and optimize complex distributed data processing systems using technologies such as Spark, Databricks, and cloud-native data services. 
• Develop canonical data models, semantic structures, and reusable datasets that support enterprise reporting and machine learning initiatives.
• Drive platform modernization initiatives (e.g., Delta Lake, streaming
  architectures, metadata-driven design).
• Provide technical leadership, guidance, and mentorship to Staff, Senior, and mid-level data engineers, enabling rapid, high-quality delivery.
• Communicate clearly and effectively with business partners to understand needs beyond surface requests. 

Must Have

• +8 years of data engineering experience.
• Expert SQL - This is a heavy SQL shop. Advanced query optimization,
  complex joins, window functions, CTEs, performance tuning.
• Excellent communication skills - Clear, articulate communication with both technical and business stakeholders. Ability to explain technical concepts and ask clarifying questions.
• Cloud data platform experience - Extensive experience with distributed
  data processing (Spark), cloud data platforms (Databricks, Synapse, or
  AWS).
• Data modeling - Strong ability to design dimensional models, data vault, canonical models across business domains.
• Production-grade data engineering - Understanding of building efficient, cost-effective queries and pipelines at scale.
• Medallion architecture - Deep understanding of bronze/silver/gold data
• transformation layers.
• Distributed systems - Designing and tuning Spark jobs, understanding
  cluster optimization and cost management.
• Python - Working knowledge (not heavily used but helpful for
  Spark/Databricks)

What We Offer

• Competitive USD salary - 8k-9k USD monthly
• 100% Remote (LATAM)
• Work embedded with a well-established enterprise product team on
  meaningful, real-world problems.