Data Platform Architect: Lakes, Warehouses & Pipelines

Zup; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Zup is seeking a Senior Data Engineer to build and evolve scalable data architectures, ensuring quality, governance and security across the data lifecycle. You will define standards, optimize ETL/ELT processes and collaborate with multidisciplinary teams to enhance data usage in the organization.

The role requires deep expertise in Data Lake/Data Warehouse/Lakehouse, strong SQL, Python/Scala, and Spark, plus cloud platform experience to support scalable data solutions that align with Zup's

Qualifications

• Advanced SQL for manipulation and analysis of large data volumes.
• Solid experience with Python or Scala applied to data engineering.
• Proven experience with Spark in distributed processing.
• Deep knowledge in architecture and implementation of Data Lake, Data Warehouse and Lakehouse.
• Practical experience with ETL/ELT tools in cloud environments.
• Advanced experience in data modeling and governance at organizational scale.
• Knowledge and experience with cloud platforms such as Azure, AWS or Google Cloud.

Responsibilities

• Build ingestion, transformation and data integration pipelines in scalable environments.
• Develop and maintain robust architectures for Data Lake, Data Warehouse and Lakehouse.
• Ensure data quality, governance and security across all lifecycle phases.
• Implement and optimize ETL/ELT processes with focus on performance and reliability.
• Define technical standards and best practices for efficient use of data platforms.
• Work on integrating multiple data sources and destinations, promoting interoperability.
• Collaborate with multidisciplinary teams to align data solutions with the organization's strategy.

Skills

SQL mastery

Python/Scala

Spark

Data architecture

ETL/ELT design

Data governance

Cloud data platforms

Tools

Azure

AWS

Google Cloud

Job description

Zup is seeking a Senior Data Engineer to build and evolve scalable data architectures, ensuring quality, governance and security across the data lifecycle. You will define standards, optimize ETL/ELT processes and collaborate with multidisciplinary teams to enhance data usage in the organization.

The role requires deep expertise in Data Lake/Data Warehouse/Lakehouse, strong SQL, Python/Scala, and Spark, plus cloud platform experience to support scalable data solutions that align with Zup's