Jobs · New Jersey

Senior Data Engineer

CoreWeave · Livingston, NJ · 3 wk ago
Hybrid$182k–$242k/yrFull-time
We need to output HTML fragment with sections: headings

for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Must not repeat job title as heading. Must not include Job ID etc. Must preserve all substantive info, remove boilerplate, navigation, legal, EEO, equal-opportunity, scam-warning, duplicated lines, application instructions. Also remove cookie/navigation/legal/EEO etc. Also remove "Wondering if you’re a good fit?" maybe that's not boilerplate? It's more like a note about fit; could be considered part of "Requirements" or "Qualifications"? Might be considered fluff but it's still substantive? It says "If some of this describes you, we’d love to talk." Might be considered part of "Qualifications" or "Preferred Experience"? Might be considered filler? The instruction: "Prefer a few substantive sections over many thin ones." We can combine. We need to extract sections: - About the role: The paragraph after "About The Role" describing responsibilities: "We're seeking a Senior Data Engineer to design and build the foundational datasets that power analytics, business intelligence, and AI across CoreWeave. You will own the development of dimensional data models, enterprise metrics, and curated data products that enable analysts, data scientists, and business stakeholders to answer complex questions with confidence. Day-to-day, you'll partner closely with business domains and analytics teams to translate operational processes into scalable data models while ensuring performance, quality, and consistency across the data ecosystem. This role combines deep data modeling expertise with strong software engineering skills across our modern lakehouse platform." That's about the role. - Responsibilities: Could be derived from "What You’ll Do" earlier: "The Data Engineering Team builds and operates the foundational data infrastructure powering analytics, AI, and operational decision-making across CoreWeave. We design resilient data pipelines, scalable lakehouse systems, and high-quality datasets that enable teams across Finance, HR, Operations, and Engineering to move faster and make smarter decisions. Our mission is to make CoreWeave's data reliable, accessible, and actionable at scale." But that's more about team mission. Might be considered responsibilities. However we already have "About The Role" which includes responsibilities. Could combine. - Requirements / Qualifications: The list under "Who You Are": Bachelor's degree..., 5+ years..., Expertise..., Advanced SQL..., Hands-on..., Experience..., Deep expertise..., Strong experience..., Preferred Experience..., etc. Also "Preferred Experience operating event-driven architectures..." etc. We need to separate required vs preferred? The instruction says use sections like Requirements, Qualifications, Skills. Could combine required qualifications into a
    . Preferred maybe also under Qualifications or Skills. - Skills: Could list programming languages, SQL, Spark/Flink, lakehouse tech, dimensional modeling, etc. But we already have those in qualifications. - Benefits: The list under "What We Offer": Medical, dental, vision insurance - 100% paid..., Company-paid Life Insurance, Voluntary supplemental life insurance, Short and long-term disability insurance, Flexible Spending Account, Health Savings Account, Tuition Reimbursement, Ability to Participate in Employee Stock Purchase Program (ESPP), Mental Wellness Benefits through Spring Health, Family-Forming support provided by Carrot, Paid Parental Leave, Flexible, full-service childcare support with Kinside, 401(k) with a generous employer match, Flexible PTO, Catered lunch each day in our office and data center locations, A casual work environment, A work culture focused on innovative disruption. Also "In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility)." So we can include that. - Pay: The base salary range: $182,000 to $242,000. Also mention discretionary bonus, equity awards. - Schedule: Not mentioned. So we should not create Schedule section. - About CoreWeave? There's a section "Why CoreWeave? About At CoreWeave, we work hard..." That's about company culture. Could be a section "About CoreWeave" but not in allowed headings list? The allowed headings are About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we should not add extra headings. Could incorporate that info into maybe "About the role" or maybe omit? The instruction: "Prefer a few substantive sections over many thin ones." We could omit the "Why CoreWeave?" section as it's not required headings. But we must preserve ALL substantive information; we cannot invent or summarize away detail. However we can embed that info within existing sections if appropriate, but we cannot create new headings not listed. The allowed headings are those; we can still include other content as paragraphs without headings? The instruction: "use

    for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It implies we should use those headings for sections, but we could also have paragraphs without headings? Probably better to stick to those headings only. However we must preserve all substantive info; we could put the "Why CoreWeave?" content under a heading like "About the role" or maybe under "Benefits"? Not ideal. Could create a section "About CoreWeave" but that's not in the list; maybe it's okay to add other headings? The instruction says "use

    for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." The "e.g." suggests those are examples, not exclusive. But later: "IMPORTANT: include a section ONLY when the posting has real, specific content for it — never emit a heading followed by filler/placeholder text". So we can create any heading as long as it's meaningful. However they gave examples; we can use those. Safer to stick to those examples. Thus we need to decide which sections to include: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay. Possibly combine some. We must not repeat job title as heading. So no

    Senior Data Engineer

    . We must not put Job ID/requisition numbers as headings. We must remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. So remove the California Applicants, EEO, Export Control Compliance, etc. Also remove "Learn more at www.coreweave.com." maybe not needed. Now craft HTML. We'll have:

    About the role

    ... (the paragraph from About The Role)

    Responsibilities

    ... (What You’ll Do paragraph)

    Qualifications

    • Bachelor's degree in Computer Science, Information Systems, or a related field (or equivalent experience)
    • 5+ years of experience designing and building analytical data models in enterprise data warehouse or lakehouse environments
    • Expertise in at least one programming language such as Python, Scala, or Rust, with experience building production-grade data systems
    • Advanced SQL skills with demonstrated experience developing, optimizing, and troubleshooting complex analytical workloads
    • Hands-on experience building and operating distributed data processing systems using Spark, Flink, or similar technologies
    • Experience working with modern lakehouse architectures and analytical technologies such as Iceberg, Delta, StarRocks, Clickhouse, or Trino
    • Deep expertise applying dimensional modeling techniques to scaled OLAP workloads
    • Strong experience building curated datasets, semantic models, and enterprise metrics that support business intelligence, advanced analytics, and AI use cases
    Maybe also include Preferred Experience as part of Qualifications or Skills. Could add a

    Preferred Experience

    but not in list. Could incorporate into Qualifications as separate bullet points prefixed with "Preferred:" but that might be okay. Better: Add a

    Skills

    for technical skills: programming languages, SQL, Spark/Flink, lakehouse tech, dimensional modeling, etc. But we already have those in Qualifications. Could combine. Given instruction to prefer few substantive sections, we could have About the role, Responsibilities, Qualifications, Benefits, Pay. We can embed responsibilities in About the role maybe. But we have both. Let's decide: - About the role: short description of role and mission. - Responsibilities: bullet list of day-to-day tasks? The posting didn't give bullet list; just paragraph. Could still be a paragraph. - Qualifications: list of required and preferred. - Benefits: list. - Pay: paragraph. We'll omit Skills separate. Now ensure we preserve all substantive info: The "Why CoreWeave?" paragraph about culture, values, growth opportunities, etc. That's substantive. Where to put? Could add a

    About CoreWeave

    but not in list. However we could incorporate into About the role? Might be okay to add a section "About CoreWeave" as it's substantive. The instruction didn't forbid other headings, just gave examples. So we can add. But to be safe, we could add a

    About CoreWeave

    paragraph. Also the "Wondering if you’re a good fit?" paragraph could be added under Qualifications or maybe a separate section "Fit". But we can incorporate into Qualifications as a note. We must not include boilerplate like "CoreWeave is an equal opportunity employer..." etc. Remove that. Also remove "Export Control Compliance" etc. Now craft HTML. We'll need to escape any special characters? Not needed. Let's write:

    About the role

    We're seeking a Senior Data Engineer to design and build the foundational datasets that power analytics, business intelligence, and AI across CoreWeave. You will own the development of dimensional data models, enterprise metrics, and curated data products that enable analysts, data scientists, and business stakeholders to answer complex questions with confidence. Day-to-day, you'll partner closely with business domains and analytics teams to translate operational processes into scalable data models while ensuring performance, quality, and consistency across the data ecosystem. This role combines deep data modeling expertise with strong software engineering skills across our modern lakehouse platform.

    Responsibilities

    The Data Engineering Team builds and operates the foundational data infrastructure powering analytics, AI, and operational decision-making across CoreWeave. We design resilient data pipelines, scalable lakehouse systems, and high-quality datasets that enable teams across Finance, HR, Operations, and Engineering to move faster and make smarter decisions. Our mission is to make CoreWeave's data reliable, accessible, and actionable at scale.

    Qualifications

    • Bachelor's degree in Computer Science, Information Systems, or a related field (or equivalent experience)
    • 5+ years of experience designing and building analytical data models in enterprise data warehouse or lakehouse environments
    • Expertise in at least one programming language such as Python, Scala, or Rust, with experience building production-grade data systems
    • Advanced SQL skills with demonstrated experience developing, optimizing, and troubleshooting complex analytical workloads
    • Hands-on experience building and operating distributed data processing systems using Spark, Flink, or similar technologies
    • Experience working with modern lakehouse architectures and analytical technologies such as Iceberg, Delta, StarRocks, Clickhouse, or Trino
    • Deep expertise applying dimensional modeling techniques to scaled OLAP workloads
    • Strong experience building curated datasets, semantic models, and enterprise metrics that support business intelligence, advanced analytics, and AI use cases
    • Preferred: Experience operating event-driven architectures using Kafka, AutoMQ, Pulsar, or similar streaming platforms
    • Preferred: Experience operating data-intensive

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