Staff Software Engineer, Data
QXO · Seattle, WA · 3 wk ago
On-siteEngineering$175k–$400k/yrFull-time
We need to output HTML fragment with sections: About the role? The posting includes intro about company, then "What You'll Do", "What You'll Bring", "What you'll earn". We need to use for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must not repeat job title as heading. We need to include sections only if posting has real specific content. So we need to map content.
We have:
- About the role: maybe the intro paragraph about QXO and mission? That's about the role? Could be "About the role" includes description of role? Actually "What You'll Do" is responsibilities. "What You'll Bring" is qualifications/skills. "What you'll earn" is benefits/pay.
We need to decide sections: Possibly "About the role" (company overview), "Responsibilities" (What You'll Do), "Qualifications" (What You'll Bring), "Benefits" (What you'll earn includes base pay, bonus, equity, 401k, insurance, PTO, etc). Also "Pay" maybe separate? But we can combine Pay and Benefits? The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We should include only those with content. We have content for About the role (company description). Responsibilities (What You'll Do). Qualifications (What You'll Bring). Benefits (What you'll earn includes benefits). Pay (base pay range). Could separate Pay and Benefits but we could combine into Benefits? However they said prefer few substantive sections over many thin ones. Could combine Pay and Benefits into one "Benefits" section that includes pay range and benefits. But they also have separate Pay heading possible. Since we have explicit base pay range, we could include a Pay section. Benefits section could include other benefits. But we might combine to avoid thin sections. Let's see: The posting includes base pay range, annual performance bonus, long term incentive, 401k, medical/dental/vision, PTO, company holidays, parental leave, paid training, legal assistance, identity protection, pet insurance, EAP. That's substantive. Could be a Benefits section that includes pay as part of benefits. But they said "never create Pay/Schedule/Benefits sections unless the posting actually states them." It does state pay range and benefits. So we could have both Pay and Benefits sections. However that might be thin? Pay section would just have base pay range and maybe bonus? Benefits section would have other benefits. That's okay.
We also have no Schedule info, so omit Schedule.
We also have no Requirements separate from Qualifications? Could combine Requirements and Qualifications? But we have Qualifications & Skills section. We'll use "Qualifications" heading for that.
We also have "Skills" maybe separate? But we can include skills within Qualifications.
We need to use
for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must not repeat job title as heading. We need to include sections only if posting has real specific content. So we need to map content.
We have:
- About the role: maybe the intro paragraph about QXO and mission? That's about the role? Could be "About the role" includes description of role? Actually "What You'll Do" is responsibilities. "What You'll Bring" is qualifications/skills. "What you'll earn" is benefits/pay.
We need to decide sections: Possibly "About the role" (company overview), "Responsibilities" (What You'll Do), "Qualifications" (What You'll Bring), "Benefits" (What you'll earn includes base pay, bonus, equity, 401k, insurance, PTO, etc). Also "Pay" maybe separate? But we can combine Pay and Benefits? The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We should include only those with content. We have content for About the role (company description). Responsibilities (What You'll Do). Qualifications (What You'll Bring). Benefits (What you'll earn includes benefits). Pay (base pay range). Could separate Pay and Benefits but we could combine into Benefits? However they said prefer few substantive sections over many thin ones. Could combine Pay and Benefits into one "Benefits" section that includes pay range and benefits. But they also have separate Pay heading possible. Since we have explicit base pay range, we could include a Pay section. Benefits section could include other benefits. But we might combine to avoid thin sections. Let's see: The posting includes base pay range, annual performance bonus, long term incentive, 401k, medical/dental/vision, PTO, company holidays, parental leave, paid training, legal assistance, identity protection, pet insurance, EAP. That's substantive. Could be a Benefits section that includes pay as part of benefits. But they said "never create Pay/Schedule/Benefits sections unless the posting actually states them." It does state pay range and benefits. So we could have both Pay and Benefits sections. However that might be thin? Pay section would just have base pay range and maybe bonus? Benefits section would have other benefits. That's okay.
We also have no Schedule info, so omit Schedule.
We also have no Requirements separate from Qualifications? Could combine Requirements and Qualifications? But we have Qualifications & Skills section. We'll use "Qualifications" heading for that.
We also have "Skills" maybe separate? But we can include skills within Qualifications.
We need to use - for any list of duties/requirements/benefits. So for responsibilities list, we need
- . For qualifications list, also list. For benefits list, also list.
We need to preserve all substantive information, not invent or summarize away detail. Must not include boilerplate like EEO, etc. Remove duplicated lines.
We need to output only HTML fragment, no /, no markdown fences.
Let's extract content.
Company intro: "QXO is a leading distributor and installer of building products serving an $800 billion market. The company’s mission is to modernize the building products industry through advanced technology and a best-in-class customer experience. QXO is North America’s largest distributor and installer of insulation, the second-largest distributor of roofing products, the second-largest publicly traded distributor of lumber and building materials, and the largest distributor of waterproofing products. The company is targeting $50 billion in annual revenue within the decade through accretive acquisitions and organic growth. For more information, visit QXO.com."
That's About the role? Could be "About the role" or maybe "About the company". We'll use About the role.
Responsibilities (What You'll Do): bullet points:
- 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.
- Develop efficient data models and ensure governance, quality, security, and compliance.
- Continuously optimize infrastructure for cost, scalability, and performance; implement CI/CD and automation for data workflows.
- Establish data engineering best practices, including testing, deployment, documentation, and metadata management.
- Build tools and frameworks to streamline data transformation and accelerate AI-driven decisionmaking; evaluate emerging technologies.
- Ensure performant systems through smart storage, caching, and streaming design choices.
We need to keep all.
Qualifications & Skills (What You'll Bring):
- Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
- 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 (MapReduce, MPP architectures, NoSQL 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.
Preferred Qualifications (maybe we can include under Qualifications as separate list? Could be separate "Preferred Qualifications" but we only have headings list: Qualifications, Skills. Could combine both required and preferred under Qualifications. But we need to preserve all info. We'll include both required and preferred as separate lists under Qualifications heading? Could have two
maybe. But we can just list all items, marking preferred? Better to keep as separate sections? The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we could have Qualifications and Skills separate. But we have both qualifications and skills mixed. Could split: Qualifications (education, years experience) and Skills (technical proficiencies). However the posting lumps them. To avoid thin sections, maybe keep one Qualifications section that includes both required and preferred. That's fine.
Benefits: from "What you'll earn": Base pay range: $175,000 - $400,000; Annual performance bonus; Long term incentive (equity/stock); 401(k) with employer match; Medical, dental, and vision insurance; PTO, company holidays, and parental leave; Paid Time Off/Paid Sick Leave: Applicants can expect to accrue 15 days of paid time off during their first year (4.62 hours for every 80 hours worked) and increased accruals after five years of service.; Paid training and certifications; Legal assistance and identity protection; Pet insurance; Employee assistance program (EAP).
We need to include Pay section maybe with base pay range and bonus and equity? But we can put all under Benefits. However they said prefer few substantive sections over many thin ones. So maybe combine Pay and Benefits into one Benefits section that includes pay range and other benefits. That seems reasonable.
Thus sections: About the role, Responsibilities, Qualifications, Benefits.
We must not include Schedule.
Now format:
About the role
QXO is a leading distributor and installer of building products serving an $800 billion market. The company’s mission is to modernize the building products industry through advanced technology and a best-in-class customer experience. QXO is North America’s largest distributor and installer of insulation, the second-largest distributor of roofing products, the second-largest publicly traded distributor of lumber and building materials, and the largest distributor of waterproofing products. The company is targeting $50 billion in annual revenue within the decade through accretive acquisitions and organic growth. For more information, visit QXO.com.
Responsibilities
- 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.
- Develop efficient data models and ensure governance, quality, security, and compliance.
- Continuously optimize infrastructure for cost, scalability, and performance; implement CI/CD and automation for data workflows.
- Establish data engineering best practices, including testing, deployment, documentation, and metadata management.
- Build tools and frameworks to streamline data transformation and accelerate AI-driven decisionmaking; evaluate emerging technologies.
- Ensure performant systems through smart storage, caching, and streaming design choices.
Qualifications
- Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
- 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 (MapReduce, MPP architectures, NoSQL databases).
- Demonstrated ability to design logical and physical data models with expertise in data warehouse optimization techniques (partitioning, distribution, indexing).
- . For qualifications list, also list. For benefits list, also list.
We need to preserve all substantive information, not invent or summarize away detail. Must not include boilerplate like EEO, etc. Remove duplicated lines.
We need to output only HTML fragment, no /, no markdown fences.
Let's extract content.
Company intro: "QXO is a leading distributor and installer of building products serving an $800 billion market. The company’s mission is to modernize the building products industry through advanced technology and a best-in-class customer experience. QXO is North America’s largest distributor and installer of insulation, the second-largest distributor of roofing products, the second-largest publicly traded distributor of lumber and building materials, and the largest distributor of waterproofing products. The company is targeting $50 billion in annual revenue within the decade through accretive acquisitions and organic growth. For more information, visit QXO.com."
That's About the role? Could be "About the role" or maybe "About the company". We'll use About the role.
Responsibilities (What You'll Do): bullet points:
- 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.
- Develop efficient data models and ensure governance, quality, security, and compliance.
- Continuously optimize infrastructure for cost, scalability, and performance; implement CI/CD and automation for data workflows.
- Establish data engineering best practices, including testing, deployment, documentation, and metadata management.
- Build tools and frameworks to streamline data transformation and accelerate AI-driven decisionmaking; evaluate emerging technologies.
- Ensure performant systems through smart storage, caching, and streaming design choices.
We need to keep all.
Qualifications & Skills (What You'll Bring):
- Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
- 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 (MapReduce, MPP architectures, NoSQL 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.
Preferred Qualifications (maybe we can include under Qualifications as separate list? Could be separate "Preferred Qualifications" but we only have headings list: Qualifications, Skills. Could combine both required and preferred under Qualifications. But we need to preserve all info. We'll include both required and preferred as separate lists under Qualifications heading? Could have two
- maybe. But we can just list all items, marking preferred? Better to keep as separate sections? The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we could have Qualifications and Skills separate. But we have both qualifications and skills mixed. Could split: Qualifications (education, years experience) and Skills (technical proficiencies). However the posting lumps them. To avoid thin sections, maybe keep one Qualifications section that includes both required and preferred. That's fine.
Benefits: from "What you'll earn": Base pay range: $175,000 - $400,000; Annual performance bonus; Long term incentive (equity/stock); 401(k) with employer match; Medical, dental, and vision insurance; PTO, company holidays, and parental leave; Paid Time Off/Paid Sick Leave: Applicants can expect to accrue 15 days of paid time off during their first year (4.62 hours for every 80 hours worked) and increased accruals after five years of service.; Paid training and certifications; Legal assistance and identity protection; Pet insurance; Employee assistance program (EAP).
We need to include Pay section maybe with base pay range and bonus and equity? But we can put all under Benefits. However they said prefer few substantive sections over many thin ones. So maybe combine Pay and Benefits into one Benefits section that includes pay range and other benefits. That seems reasonable.
Thus sections: About the role, Responsibilities, Qualifications, Benefits.
We must not include Schedule.
Now format:
- 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.
- Develop efficient data models and ensure governance, quality, security, and compliance.
- Continuously optimize infrastructure for cost, scalability, and performance; implement CI/CD and automation for data workflows.
- Establish data engineering best practices, including testing, deployment, documentation, and metadata management.
- Build tools and frameworks to streamline data transformation and accelerate AI-driven decisionmaking; evaluate emerging technologies.
- Ensure performant systems through smart storage, caching, and streaming design choices.
- Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
- 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 (MapReduce, MPP architectures, NoSQL databases).
- Demonstrated ability to design logical and physical data models with expertise in data warehouse optimization techniques (partitioning, distribution, indexing).
About the role
QXO is a leading distributor and installer of building products serving an $800 billion market. The company’s mission is to modernize the building products industry through advanced technology and a best-in-class customer experience. QXO is North America’s largest distributor and installer of insulation, the second-largest distributor of roofing products, the second-largest publicly traded distributor of lumber and building materials, and the largest distributor of waterproofing products. The company is targeting $50 billion in annual revenue within the decade through accretive acquisitions and organic growth. For more information, visit QXO.com.
Responsibilities
Qualifications