Senior Data Warehouse Engineer

Senior Data Warehouse Engineer

Pando (www.pando.ai) is pioneering the future of autonomous logistics with innovative AI capabilities. Trusted by Fortune 500 enterprises with global customers across North America, Europe, and Asia Pacific regions, we are leading the global disruption of supply chain software, with our AI-powered, no-code, & unified platform empowering Autonomous Supply Chain.

We have been recognized by Gartner for our transportation management capabilities, by the World Economic Forum (WEF) as a Technology Pioneer, by G2 as a Market Leader in Freight Management, and named one of the fastest-growing technology companies by Deloitte.

Why Pando?

We are one of the fastest growing companies reimagining supply chain and logistics for Manufacturers & Retailers scaling up globally. We are a growing team, unrelenting and enthusiastic about building great products. We have folks who are pragmatic, imaginative or a quirky combination of both. We yearn for purpose in our work & support. Each other to grow. We work extremely hard with people we respect and admire, and we play to win.

As a Senior AI and Data Warehouse Engineer at Pando, you will be responsible for building and scaling the data and AI services team. You will drive the design and implementation of highly scalable, modular, and reusable data pipelines, leveraging big data technologies and low-code implementations. This is a senior leadership position where you will work closely with cross-functional teams to deliver solutions that power advanced analytics, dashboards, and AI-based insights.

Key Responsibilities

• Lead the development of scalable, high-performance data pipelines using PySpark or Big Data ETL pipeline technologies.
• Drive data modeling 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

• 4 to 6 years of experience in big data and AI technologies, with expertise in PySpark or similar Big Data ETL pipeline technologies.
• 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.