Manager, Data Engineering
for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must include sections only if posting has real specific content. We have:
- About the role: The initial description paragraph(s) before "Primary Responsibilities". That is about the role. So we can have About the role
with paragraphs.
- Responsibilities: "Primary Responsibilities:" list bullet points. So we can have Responsibilities
with - items.
- Qualifications: The "Qualifications" section lists bullet points. So
Qualifications
with list.
- Skills: Not explicitly separate; qualifications include skills. Could we create Skills section? The posting does not have a separate Skills heading; but we could extract skills from qualifications? However instruction: include a section ONLY when the posting has real, specific content for it. There's no explicit Skills section; but we could treat Qualifications as skills? But we already have Qualifications. Better not to create Skills if not present.
- Benefits: The posting mentions benefits in "Additional Information": medical, dental, vision benefits starting day 1 + 401k and PTO. Also later "Why work for Cornerstone Building Brands?" includes benefits list. So we have benefits content. So we can have Benefits
with list.
- Pay: The posting includes salary range: "The US base salary range for this full-time position is $145,000 - $165,000 + bonus + medical, dental, vision benefits starting day 1 + 401k and PTO." So we have pay info. So Pay
with paragraph.
- Schedule: Not mentioned besides full-time defined as 30+ hours per week. That's schedule info. Could we create Schedule section? The posting mentions full-time definition. That's schedule info. So we could include Schedule with paragraph about full-time definition. However we must avoid filler like "not specified". It is specified: full-time defined as regularly working 30+ hours per week. So we can include Schedule.
- Requirements: Not separate; qualifications cover. Could we have Requirements? Not present. So skip.
We must not repeat job title as heading. Not include Job ID etc.
We must remove boilerplate: EEO, legal, scam warning, etc. Also remove "Additional Information" heading? We'll incorporate relevant info into Benefits, Pay, Schedule.
We must preserve all substantive information; do not invent or summarize away detail. So we need to keep details: e.g., bullet points under Responsibilities, Qualifications, Benefits list, Pay details, Schedule definition.
We need to output only HTML fragment, no /, no markdown fences.
Let's extract content.
About the role: The paragraph(s) before "Primary Responsibilities:":
"Cornerstone Building Brands is a leading manufacturer of exterior building products for residential and low-rise non-residential buildings in North America. Headquartered in Cary, N.C., we serve residential and commercial customers across the new construction and Repair & Remodel (R&R) markets. Our market-leading portfolio of products spans vinyl windows, vinyl siding, stone veneer, metal roofing, metal wall systems and metal accessories. Cornerstone Building Brands’ broad, multi-channel distribution platform and expansive national footprint includes more than 18,800 team members at manufacturing, distribution and office locations throughout North America. Corporate stewardship and Environmental, Social and Governance (ESG) responsibility are embedded in our culture. We are committed to contributing positively to the communities where we live, work and play. For more information, visit us at http://cornerstonebuildingbrands.com. Job Description We're looking for a hands-on data engineer to own, maintain and expand the data infrastructure behind our Siding & Accessories commercial analytics function. This is not a business analyst role that touches data occasionally — it's a technical role that puts you in the database every day, writing queries, building and maintaining pipelines, curating the master and reference data everything joins to, and guaranteeing the integrity of the data that sales, product, customer, and market reporting depend on. You will own the commercial database from day one. You'll manage the SQL Server environment, keep data flowing cleanly from our source systems into the models and dashboards the business runs on, and build the pipelines that bring together sales, product, customer, and external market data into one trusted commercial dataset. Just as important, you'll own the master and reference data — the customer, product, and territory definitions everything reconciles to — so the numbers tie out no matter who's asking. If you've owned a production database, built and troubleshot data pipelines end to end, and can write SQL in your sleep, this role is for you."
We need to keep that as prose in . Possibly split into multiple paragraphs but okay.
Responsibilities: list after "Primary Responsibilities:":
- Own and maintain the commercial SQL Server database — tables, views, stored procedures, data integrity, and performance.
- Write, optimize, and troubleshoot SQL queries daily. This is hands-on work, not oversight.
- Own the end-to-end data flow: source systems (JDE and others) → SQL Server commercial database → Power BI. Ensure data moves correctly, transformations are accurate, and outputs are validated before they reach stakeholders.
- Build and maintain ingestion for external, third-party market data (industry, competitive, and share sources) and join it cleanly to internal sales, product, and customer data — reconciling keys, grain, and definitions across sources.
- Monitor and respond to production incidents independently — pipeline failures, file failures, data quality issues. You triage, engage the right teams, and communicate status. You don't wait for someone to tell you what to do.
- Own the data validation and quality assurance process. If data goes out wrong, it's on you to catch it first.
- Own the master and reference data behind commercial reporting — customer, product, and sales-hierarchy / territory (e.g., TSM / RSM) masters — so every downstream model joins to one consistent, trusted set of definitions.
- Build and maintain the crosswalks and mapping tables that reconcile codes and hierarchies across source systems, and between internal data and external market data.
- Standardize, de-duplicate, and validate reference data, and enforce clear definitions and naming so the same entity means the same thing everywhere it's used.
- Manage changes to master and reference data with an eye to history — version or effective-date changes so a mapping update doesn't silently rewrite prior reporting.
- Act as data steward for these datasets: document what they are, who owns them, and how they refresh, and be the point of contact when a definition or hierarchy is in question.
- Design, build, and expand data pipelines across the four commercial domains — sales, market, product, and customer — as reporting and analytics needs grow.
- Stand up and operationalize ingestion for external market data feeds (APIs, purchased datasets, scheduled files), including refresh cadence, error handling, and lineage.
- Document and reverse-engineer existing transformation logic, and improve the architecture for reliability, performance, and maintainability.
- Evaluate and adopt ETL / integration tooling where it strengthens the pipeline, and reduce brittle or undocumented dependencies over time.
- Serve as the data expert for the Commercial Analytics team — translate business needs into data requirements and explain data outputs in business terms.
- Partner with the Director of Customer Data & Analytics and business stakeholders to ensure the data infrastructure supports commercial operations and decisions.
- Coordinate with source-system owners and IT partners to secure reliable, well-understood data feeds.
We'll put each as
- .
Qualifications: list after "Qualifications":
- 7+ years of hands-on SQL Server experience.
- Hands-on experience with JD Edwards (JDE).
- Proficiency with Python for data work.
- Experience managing and maintaining a production database.
- Strong understanding of data flow and integration between systems.
- Experience integrating data from multiple sources.
- Experience owning master or reference data.
- Experience with data validation and quality assurance.
- Independent problem-solving and operational ownership.
- Experience leading or contributing to a data platform build or migration.
- Experience with ETL tools or integration platforms (SSIS, Azure Data Factory, Boomi, Informatica, or similar).
- Experience ingesting external / third-party data (industry, market, competitive, or share data) via APIs, purchased datasets, or scheduled files.
- Familiarity with Power BI (or Tableau) and an understanding of what downstream reporting needs from a clean data model.
- Exposure to master data management (MDM) or data governance practices — stewardship, reference-data versioning, or maintaining a canonical set of business definitions.
- Experience with cloud data platforms (Snowflake, Azure, AWS).
- Experience in manufacturing, building products, or B2B distribution industries.
- Familiarity with R or other analytics/scripting languages beyond Python.
We'll list.
Benefits: from Additional Information and "Why work for Cornerstone Building Brands?":
- medical, dental and vision benefits starting day 1
- PTO
- paid holidays
- FSA
- life insurance
- LTD
- STD
- 401k
- EAP
- discount programs
- tuition reimbursement
- training
- professional development
Also note: "Full-time* team members receive** medical, dental and vision benefits starting day 1." plus other benefits list.
We'll include these as list items.
Pay: The US base salary range for this full-time position is $145,000 - $165,000 + bonus + medical, dental, vision benefits starting day 1 + 401k and PTO. Also note: "Our salary ranges are determined by role, level, and location. Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process." We'll include that as prose.
Schedule: "Full-time is defined as regularly working 30+ hours per week." Also appears twice. We'll include that.
We must not include boilerplate like EEO, scam warning, CCPA, etc. Also remove "Note to External Recruiters", "Notice of Recruitment Fraud", etc.
Now construct HTML.
We'll have:
About the role
... (the paragraph)
Responsibilities
- ...
...
Qualifications
- ...
...
Benefits
- ...
...
Pay
... (salary range etc)
Schedule
Full-time is defined as regularly working 30+ hours per week.
Make sure to not include extra sections like Skills.
Check that we haven't missed any substantive info: The description about "Cornerstone Building Brands is a leading manufacturer..." includes info about company; we kept that.
We also kept the Job Description sentence about "We're looking for a hands-on data engineer..." etc.
We kept all responsibilities bullet points.
We kept all qualifications bullet points.
We kept benefits list.
We kept pay details.
We kept schedule definition.
We omitted any duplicated lines.
Now produce HTML.
Be careful to escape any HTML special characters like &, <, >. In the text we have arrows →, and symbols like —, etc. Those are okay as Unicode; we can keep them. The ampersand in "JDE and others" is fine. The "&" in "SSIS, Azure Data Factory, Boomi, Informatica, or similar" no ampersand. The "R or other analytics/scripting languages beyond Python." fine.
The bullet list includes "—" em dash; okay.
We'll output.
Let's craft.
Qualifications
with list. - Skills: Not explicitly separate; qualifications include skills. Could we create Skills section? The posting does not have a separate Skills heading; but we could extract skills from qualifications? However instruction: include a section ONLY when the posting has real, specific content for it. There's no explicit Skills section; but we could treat Qualifications as skills? But we already have Qualifications. Better not to create Skills if not present. - Benefits: The posting mentions benefits in "Additional Information": medical, dental, vision benefits starting day 1 + 401k and PTO. Also later "Why work for Cornerstone Building Brands?" includes benefits list. So we have benefits content. So we can haveBenefits
with list. - Pay: The posting includes salary range: "The US base salary range for this full-time position is $145,000 - $165,000 + bonus + medical, dental, vision benefits starting day 1 + 401k and PTO." So we have pay info. SoPay
with paragraph. - Schedule: Not mentioned besides full-time defined as 30+ hours per week. That's schedule info. Could we create Schedule section? The posting mentions full-time definition. That's schedule info. So we could include Schedule with paragraph about full-time definition. However we must avoid filler like "not specified". It is specified: full-time defined as regularly working 30+ hours per week. So we can include Schedule. - Requirements: Not separate; qualifications cover. Could we have Requirements? Not present. So skip. We must not repeat job title as heading. Not include Job ID etc. We must remove boilerplate: EEO, legal, scam warning, etc. Also remove "Additional Information" heading? We'll incorporate relevant info into Benefits, Pay, Schedule. We must preserve all substantive information; do not invent or summarize away detail. So we need to keep details: e.g., bullet points under Responsibilities, Qualifications, Benefits list, Pay details, Schedule definition. We need to output only HTML fragment, no /, no markdown fences. Let's extract content. About the role: The paragraph(s) before "Primary Responsibilities:": "Cornerstone Building Brands is a leading manufacturer of exterior building products for residential and low-rise non-residential buildings in North America. Headquartered in Cary, N.C., we serve residential and commercial customers across the new construction and Repair & Remodel (R&R) markets. Our market-leading portfolio of products spans vinyl windows, vinyl siding, stone veneer, metal roofing, metal wall systems and metal accessories. Cornerstone Building Brands’ broad, multi-channel distribution platform and expansive national footprint includes more than 18,800 team members at manufacturing, distribution and office locations throughout North America. Corporate stewardship and Environmental, Social and Governance (ESG) responsibility are embedded in our culture. We are committed to contributing positively to the communities where we live, work and play. For more information, visit us at http://cornerstonebuildingbrands.com. Job Description We're looking for a hands-on data engineer to own, maintain and expand the data infrastructure behind our Siding & Accessories commercial analytics function. This is not a business analyst role that touches data occasionally — it's a technical role that puts you in the database every day, writing queries, building and maintaining pipelines, curating the master and reference data everything joins to, and guaranteeing the integrity of the data that sales, product, customer, and market reporting depend on. You will own the commercial database from day one. You'll manage the SQL Server environment, keep data flowing cleanly from our source systems into the models and dashboards the business runs on, and build the pipelines that bring together sales, product, customer, and external market data into one trusted commercial dataset. Just as important, you'll own the master and reference data — the customer, product, and territory definitions everything reconciles to — so the numbers tie out no matter who's asking. If you've owned a production database, built and troubleshot data pipelines end to end, and can write SQL in your sleep, this role is for you." We need to keep that as prose in. Possibly split into multiple paragraphs but okay. Responsibilities: list after "Primary Responsibilities:": - Own and maintain the commercial SQL Server database — tables, views, stored procedures, data integrity, and performance. - Write, optimize, and troubleshoot SQL queries daily. This is hands-on work, not oversight. - Own the end-to-end data flow: source systems (JDE and others) → SQL Server commercial database → Power BI. Ensure data moves correctly, transformations are accurate, and outputs are validated before they reach stakeholders. - Build and maintain ingestion for external, third-party market data (industry, competitive, and share sources) and join it cleanly to internal sales, product, and customer data — reconciling keys, grain, and definitions across sources. - Monitor and respond to production incidents independently — pipeline failures, file failures, data quality issues. You triage, engage the right teams, and communicate status. You don't wait for someone to tell you what to do. - Own the data validation and quality assurance process. If data goes out wrong, it's on you to catch it first. - Own the master and reference data behind commercial reporting — customer, product, and sales-hierarchy / territory (e.g., TSM / RSM) masters — so every downstream model joins to one consistent, trusted set of definitions. - Build and maintain the crosswalks and mapping tables that reconcile codes and hierarchies across source systems, and between internal data and external market data. - Standardize, de-duplicate, and validate reference data, and enforce clear definitions and naming so the same entity means the same thing everywhere it's used. - Manage changes to master and reference data with an eye to history — version or effective-date changes so a mapping update doesn't silently rewrite prior reporting. - Act as data steward for these datasets: document what they are, who owns them, and how they refresh, and be the point of contact when a definition or hierarchy is in question. - Design, build, and expand data pipelines across the four commercial domains — sales, market, product, and customer — as reporting and analytics needs grow. - Stand up and operationalize ingestion for external market data feeds (APIs, purchased datasets, scheduled files), including refresh cadence, error handling, and lineage. - Document and reverse-engineer existing transformation logic, and improve the architecture for reliability, performance, and maintainability. - Evaluate and adopt ETL / integration tooling where it strengthens the pipeline, and reduce brittle or undocumented dependencies over time. - Serve as the data expert for the Commercial Analytics team — translate business needs into data requirements and explain data outputs in business terms. - Partner with the Director of Customer Data & Analytics and business stakeholders to ensure the data infrastructure supports commercial operations and decisions. - Coordinate with source-system owners and IT partners to secure reliable, well-understood data feeds. We'll put each as
About the role
... (the paragraph)
Responsibilities
- ... ...
Qualifications
- ... ...
Benefits
- ... ...
Pay
... (salary range etc)
Schedule
Full-time is defined as regularly working 30+ hours per week.
Make sure to not include extra sections like Skills. Check that we haven't missed any substantive info: The description about "Cornerstone Building Brands is a leading manufacturer..." includes info about company; we kept that. We also kept the Job Description sentence about "We're looking for a hands-on data engineer..." etc. We kept all responsibilities bullet points. We kept all qualifications bullet points. We kept benefits list. We kept pay details. We kept schedule definition. We omitted any duplicated lines. Now produce HTML. Be careful to escape any HTML special characters like &, <, >. In the text we have arrows →, and symbols like —, etc. Those are okay as Unicode; we can keep them. The ampersand in "JDE and others" is fine. The "&" in "SSIS, Azure Data Factory, Boomi, Informatica, or similar" no ampersand. The "R or other analytics/scripting languages beyond Python." fine. The bullet list includes "—" em dash; okay. We'll output. Let's craft.