Data Architect

Key Responsibilities

• Lead the development of scalable, high-performance data pipelines using PySpark or Big Data ETL pipeline technologies.
• Drive data modelling efforts for analytics, dashboards, and knowledge graphs.
• Oversee the implementation of parquet-based data lakes.
• Work on OLAP databases, ensuring optimal data structure for reporting and querying.
• Architect and optimize large-scale enterprise big data implementations with a focus on modular and reusable low-code libraries.
• Collaborate with stakeholders to design and deliver AI and DWH solutions that align with business needs.
• Mentor and lead a team of engineers, building out the data and AI services organization.

Requirements

• 8 + years of experience in big data and AI technologies, with expertise in PySpark or similar Big Data ETL pipeline technologies.
• Experience with AWS & services like EMR.
• Familiarity with Iceberg, Dremio tools
• Strong proficiency in SQL and OLAP database technologies.
• Firsthand experience with data modeling for analytics, dashboards, and knowledge graphs.
• Proven experience with parquet-based data lake implementations.
• Expertise in building highly scalable, high-volume data pipelines.
• Experience with modular, reusable, low-code-based implementations.
• Involvement in large-scale enterprise big data implementations.
• Initiative-taker with strong motivation and the ability to lead a growing team.

Preferred

• Experience leading a team or building out a new department.
• Experience with cloud-based data platforms and AI services.
• Familiarity with supply chain technology or fulfilment platforms is a plus.