Data Engineer

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This range is provided by QXO. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$/yr - $/yr

Annual Bonus, Sign-on bonus, and RSUs

At QXO, we are redefining digital commerce. Our mission is to deliver seamless, intelligent, and scalable eCommerce experiences through next‑generation software systems. Our engineering teams build distributed platforms that power critical services such as customer identity, product discovery, checkout, and personalization. If you thrive in ambiguous environments, care deeply about performance and scalability, and are driven by customer impact — we want you on our team.

We’re seeking a Senior Data Engineer who will take ownership of our data architecture and serve as a technical leader. You will work on ambiguous problems with limited guidance, influence team technical strategy, and drive data engineering excellence. This role demands someone who thinks architecturally, proactively fixes deficiencies, and makes complex systems simpler while building solutions that are exemplary in security, maintainability, scalability, চলছে।

You’ll be responsible for designing and maintaining our enterprise data warehouse and data infrastructure that enables analytics, reporting, and business intelligence across the organization.

This role is ideal for engineers who are highly technical, customer‑obsessed, and comfortable working in fast‑paced environments with high ambiguity and high ownership.

• Take ownership of team data architecture, including data warehouse design, providing system‑wide design guidance and ensuring data is auditable, available, and accessible.
• Design and deploy large‑scale data solutions including data warehouse implementations in ambiguous problem areas with significant impact on data quality, availability, or business value.
• Lead logical and physical data model design for data warehouse and data lakes, optimizing query performance, storage efficiency, and data integrity.
• Anticipate data access patterns and proactively remove bottlenecks, ensuring smooth data flow from operational sources to data warehouse and analytical endpoints.
• Drive data engineering best practices including Data Discovery, Naming Conventions, Data Quality frameworks, Operational Excellence, and Security standards.
• Make architectural trade‑offs between short‑term technology needs and long‑term business needs (build vs. buy, storage strategies, data warehouse vs. data lake technologies).
• Lead design reviews for team solutions and related software systems, bringing clarity to complexity and fostering shared understanding.
• Build consensus across discordant views and resolve root causes of endemic problems, including those that unblock innovation of related teams.
• Mentor and develop engineers, improving their technical skills and understanding of data engineering best practices.
• Provide technical assessments for promotion candidates and participate in hiring processes.

• 7+ years of data engineering experience building data infrastructure, data warehouses, pipelines, and analytics solutions at scale.
• Proven track record delivering large data solutions (data warehouse implementations, data models, architectures, data flows) in difficult or ambiguous problem areas.
• Deep proficiency in SQL and at least one programming language (Python, R) for data processing and orchestration.
• Strong understanding of distributed systems (Map Reduce, MPP architectures, No
  
  SQL databases).
• Demonstrated ability to design logical and physical data models with expertise in data warehouse optimization techniques (partitioning, distribution, indexing).
• Experience with data persistence technologies including modern data warehouses and integration patterns (ETL, streaming, federation).
• Track record of taking ownership of data architecture and driving simplification.
• Strong ability to communicate technical ideas, build consensus, and influence technical strategy.

• Bachelor’s degree in computer…