Staff Data Platform Engineer
for section headings. Use - for any list of duties/requirements/benefits, and
for prose. Do NOT repeat job title as heading. Do NOT put Job ID/requisition numbers as headings. Remove boilerplate, navigation, legal, EEO, equal-opportunity, scam-warning, duplicated lines, application instructions. Preserve all substantive information; do not invent or summarize away detail. Include a section only when posting has real, specific content for it; never emit heading followed by filler/placeholder text (e.g., "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless posting actually states them. Prefer a few substantive sections over many thin ones.
We need to parse the job description.
Key sections:
- About the role: The description includes a paragraph: "Noetica is an AI-native legal technology company, now part of Thomson Reuters, that transforms complex corporate transaction data into structured, searchable market intelligence. Its platform helps legal and finance professionals analyze deal terms, identify market trends, and assess risk with greater speed and confidence. As a Staff Data Platform Engineer, you will set the technical direction for Noetica’s data infrastructure and lead the evolution of systems that process legal and financial document data at significant scale. This hands-on technical leadership role combines architecture, implementation, cross-functional influence, and team development to ensure the platform supports rapid AI innovation while meeting demanding reliability, security, and compliance standards."
That's about the role.
- Responsibilities: List of key responsibilities bullet points: "Own the technical roadmap for the data platform, balancing scalability, reliability, security, compliance, and business priorities. Architect next-generation pipelines and storage systems for high-volume document data. Lead decisions on technology selection, system design, and infrastructure strategy across the platform. Advance data governance, privacy controls, compliance frameworks, and audit capabilities for regulated data. Partner with machine learning and AI leaders to enable model training, evaluation, and inference at scale. Establish technical standards, mentor engineers, and help build a high-performing platform organization. Represent the platform function in company-wide architecture and engineering decisions. Remain hands-on by owning critical systems and contributing code to solve complex technical challenges."
- Required Qualifications: list: "Ten or more years of software engineering experience, including at least six years focused on data platforms, infrastructure, or large-scale backend systems. Demonstrated expertise architecting distributed systems, including high-throughput pipelines and petabyte-scale or similarly complex data processing environments. Deep knowledge of big data technologies, distributed databases, and modern data platforms. Strong systems programming skills in Python, Java, C++, Rust, or Go, with experience delivering production systems. Expertise in data compliance, privacy engineering, and secure data handling in regulated environments. Experience building and mentoring engineering teams and driving complex technical initiatives to completion. Sound judgment in balancing engineering quality, delivery speed, cost, risk, and business impact."
- Preferred Qualifications: list: "Experience in a high-growth environment where platform infrastructure was critical to business success. A record of leading major architectural transitions or platform migrations. Published technical writing or public speaking on data systems, architecture, or engineering practices. Experience with machine learning infrastructure, feature stores, or platforms that support AI workloads. Background in legal technology, financial services, or another highly regulated industry. Coding in Python"
- Benefits: The "What’s in it For You?" section includes many benefits: Hybrid Work Model, Flexibility & Work-Life Balance, Career Development and Growth, Industry Competitive Benefits, Culture, Social Impact, Making a Real-World Impact, plus Thomson Reuters benefits details: health, dental, vision, disability, life insurance, 401k, vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave, optional hospital, accident and sickness insurance, optional life and AD&D insurance, Flexible Spending and Health Savings Accounts, fitness reimbursement, access to Employee Assistance Program, Group Legal Identity Theft Protection benefit, access to 529 Plan, commuter benefits, Adoption & Surrogacy Assistance, Tuition Reimbursement, access to Employee Stock Purchase Plan.
We need to include Benefits section only if posting actually states them. Yes, they do. So we can include a Benefits section with a list.
- Pay: The posting states: "The base compensation range for the role in any of those locations is $146,800 USD - $272,600 USD." Also mentions eligibility for Annual Bonus. So we can include Pay section with that info.
- Schedule: The posting mentions hybrid work model, flexible work arrangements, work from anywhere for up to 8 weeks per year. That's schedule/flexibility. So we could include Schedule section describing hybrid work model, flexible work arrangements, work from anywhere up to 8 weeks per year. However the instruction says: never create Pay/Schedule/Benefits sections unless posting actually states them. It does state hybrid work model and flexible work arrangements, so we can include Schedule.
But we need to prefer a few substantive sections over many thin ones. Could combine Benefits and Pay? But they are separate categories. The instruction says use headings for those categories if content exists. We have content for About the role, Responsibilities, Required Qualifications, Preferred Qualifications, Benefits, Pay, Schedule. That's many sections but each has substantive content. Could we combine Required and Preferred Qualifications into a single Qualifications section? The instruction says use headings like Qualifications, Skills, Benefits, Pay, Schedule. It lists Qualifications as a possible heading. So we could have a Qualifications section that includes both required and preferred. That would reduce number of sections. Similarly Skills could be separate but we have skills mentioned in qualifications (programming languages). Could incorporate into Qualifications.
Thus we could have sections: About the role, Responsibilities, Qualifications, Benefits, Pay, Schedule. That's six sections.
We need to ensure we don't include filler like "commensurate with experience". Not present.
We need to remove boilerplate: EEO, equal-opportunity, scam-warning, application instructions, navigation, cookie, legal. The posting includes a lot of EEO statements at the end: "As a global business, we rely on the unique backgrounds..." etc. Also includes accommodation contact, fraud warning, etc. We must remove those.
Also remove duplicated lines.
We must preserve all substantive information. So we need to keep the benefits details, pay range, schedule details, etc.
Now produce HTML fragment: no or , no markdown fences.
We'll output something like:
About the role
Noetica is an AI-native legal technology company, now part of Thomson Reuters, that transforms complex corporate transaction data into structured, searchable market intelligence. Its platform helps legal and finance professionals analyze deal terms, identify market trends, and assess risk with greater speed and confidence. As a Staff Data Platform Engineer, you will set the technical direction for Noetica’s data infrastructure and lead the evolution of systems that process legal and financial document data at significant scale. This hands-on technical leadership role combines architecture, implementation, cross-functional influence, and team development to ensure the platform supports rapid AI innovation while meeting demanding reliability, security, and compliance standards.
Responsibilities
- Own the technical roadmap for the data platform, balancing scalability, reliability, security, compliance, and business priorities.
- Architect next-generation pipelines and storage systems for high-volume document data.
- Lead decisions on technology selection, system design, and infrastructure strategy across the platform.
- Advance data governance, privacy controls, compliance frameworks, and audit capabilities for regulated data.
- Partner with machine learning and AI leaders to enable model training, evaluation, and inference at scale.
- Establish technical standards, mentor engineers, and help build a high-performing platform organization.
- Represent the platform function in company-wide architecture and engineering decisions.
- Remain hands-on by owning critical systems and contributing code to solve complex technical challenges.
Qualifications
Required:
- Ten or more years of software engineering experience, including at least six years focused on data platforms, infrastructure, or large-scale backend systems.
- Demonstrated expertise architecting distributed systems, including high-throughput pipelines and petabyte-scale or similarly complex data processing environments.
- Deep knowledge of big data technologies, distributed databases, and modern data platforms.
- Strong systems programming skills in Python, Java, C++, Rust, or Go, with experience delivering production systems.
- Expertise in data compliance, privacy engineering, and secure data handling in regulated environments.
- Experience building and mentoring engineering teams and driving complex technical initiatives to completion.
- Sound judgment in balancing engineering quality, delivery speed, cost, risk, and business impact.
Preferred:
- Experience in a high-growth environment where platform infrastructure was critical to business success.
- A record of leading major architectural transitions or platform migrations.
- Published technical writing or public speaking on data systems, architecture, or engineering practices.
- Experience with machine learning infrastructure, feature stores, or platforms that support AI workloads.
- Background in legal technology, financial services, or another highly regulated industry.
- Coding in Python.
Benefits
- Hybrid Work Model: flexible hybrid working environment for office‑based roles while delivering a seamless experience that is digitally and physically connected.
- Flexibility & Work‑Life Balance: Flex My Way policies, work‑from‑anywhere for up to 8 weeks per year, supportive workplace policies to manage personal and professional responsibilities.
- Career Development and Growth: Grow My Way programming, skills‑first approach, continuous learning.
- Industry Competitive Benefits: comprehensive benefit plans including flexible vacation, two company‑wide Mental Health Days off, access to Headspace app, retirement savings, tuition reimbursement, employee incentive programs, resources for mental, physical, and financial wellbeing.
- Culture: globally recognized award‑winning reputation for inclusion, belonging, flexibility, work‑life balance.
- Social Impact: Social Impact Institute, two paid volunteer days off annually, pro‑bono consulting projects, ESG initiatives.
- Making a Real‑World Impact: helping customers pursue justice, truth, transparency; upholding rule of law, turning wheels of commerce, catching bad actors, reporting facts, providing trusted unbiased information worldwide.
- Thomson Reuters benefits: market‑competitive health, dental, vision, disability, life insurance; competitive 401k with company match; market‑leading work‑life benefits including vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave; optional hospital, accident and sickness insurance (employee‑paid); optional life and AD&D insurance (employee‑paid); Flexible Spending and Health Savings Accounts; fitness reimbursement; access to Employee Assistance Program; Group Legal Identity Theft Protection benefit (employee‑paid); access to 529 Plan; commuter benefits; Adoption & Surrogacy Assistance; Tuition Reimbursement; access to Employee Stock Purchase Plan.
Pay
The base compensation range for the role in any of the eligible locations (New York City, San Francisco, Los Angeles, Irvine, CA; McLean, VA; Washington, DC) is $146,800 USD – $272,600 USD. Base pay is positioned within the range based on knowledge, skills, experience and internal equity. The role may also be eligible for an Annual Bonus based on enterprise
for prose. Do NOT repeat job title as heading. Do NOT put Job ID/requisition numbers as headings. Remove boilerplate, navigation, legal, EEO, equal-opportunity, scam-warning, duplicated lines, application instructions. Preserve all substantive information; do not invent or summarize away detail. Include a section only when posting has real, specific content for it; never emit heading followed by filler/placeholder text (e.g., "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless posting actually states them. Prefer a few substantive sections over many thin ones. We need to parse the job description. Key sections: - About the role: The description includes a paragraph: "Noetica is an AI-native legal technology company, now part of Thomson Reuters, that transforms complex corporate transaction data into structured, searchable market intelligence. Its platform helps legal and finance professionals analyze deal terms, identify market trends, and assess risk with greater speed and confidence. As a Staff Data Platform Engineer, you will set the technical direction for Noetica’s data infrastructure and lead the evolution of systems that process legal and financial document data at significant scale. This hands-on technical leadership role combines architecture, implementation, cross-functional influence, and team development to ensure the platform supports rapid AI innovation while meeting demanding reliability, security, and compliance standards." That's about the role. - Responsibilities: List of key responsibilities bullet points: "Own the technical roadmap for the data platform, balancing scalability, reliability, security, compliance, and business priorities. Architect next-generation pipelines and storage systems for high-volume document data. Lead decisions on technology selection, system design, and infrastructure strategy across the platform. Advance data governance, privacy controls, compliance frameworks, and audit capabilities for regulated data. Partner with machine learning and AI leaders to enable model training, evaluation, and inference at scale. Establish technical standards, mentor engineers, and help build a high-performing platform organization. Represent the platform function in company-wide architecture and engineering decisions. Remain hands-on by owning critical systems and contributing code to solve complex technical challenges." - Required Qualifications: list: "Ten or more years of software engineering experience, including at least six years focused on data platforms, infrastructure, or large-scale backend systems. Demonstrated expertise architecting distributed systems, including high-throughput pipelines and petabyte-scale or similarly complex data processing environments. Deep knowledge of big data technologies, distributed databases, and modern data platforms. Strong systems programming skills in Python, Java, C++, Rust, or Go, with experience delivering production systems. Expertise in data compliance, privacy engineering, and secure data handling in regulated environments. Experience building and mentoring engineering teams and driving complex technical initiatives to completion. Sound judgment in balancing engineering quality, delivery speed, cost, risk, and business impact." - Preferred Qualifications: list: "Experience in a high-growth environment where platform infrastructure was critical to business success. A record of leading major architectural transitions or platform migrations. Published technical writing or public speaking on data systems, architecture, or engineering practices. Experience with machine learning infrastructure, feature stores, or platforms that support AI workloads. Background in legal technology, financial services, or another highly regulated industry. Coding in Python" - Benefits: The "What’s in it For You?" section includes many benefits: Hybrid Work Model, Flexibility & Work-Life Balance, Career Development and Growth, Industry Competitive Benefits, Culture, Social Impact, Making a Real-World Impact, plus Thomson Reuters benefits details: health, dental, vision, disability, life insurance, 401k, vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave, optional hospital, accident and sickness insurance, optional life and AD&D insurance, Flexible Spending and Health Savings Accounts, fitness reimbursement, access to Employee Assistance Program, Group Legal Identity Theft Protection benefit, access to 529 Plan, commuter benefits, Adoption & Surrogacy Assistance, Tuition Reimbursement, access to Employee Stock Purchase Plan. We need to include Benefits section only if posting actually states them. Yes, they do. So we can include a Benefits section with a list. - Pay: The posting states: "The base compensation range for the role in any of those locations is $146,800 USD - $272,600 USD." Also mentions eligibility for Annual Bonus. So we can include Pay section with that info. - Schedule: The posting mentions hybrid work model, flexible work arrangements, work from anywhere for up to 8 weeks per year. That's schedule/flexibility. So we could include Schedule section describing hybrid work model, flexible work arrangements, work from anywhere up to 8 weeks per year. However the instruction says: never create Pay/Schedule/Benefits sections unless posting actually states them. It does state hybrid work model and flexible work arrangements, so we can include Schedule. But we need to prefer a few substantive sections over many thin ones. Could combine Benefits and Pay? But they are separate categories. The instruction says use headings for those categories if content exists. We have content for About the role, Responsibilities, Required Qualifications, Preferred Qualifications, Benefits, Pay, Schedule. That's many sections but each has substantive content. Could we combine Required and Preferred Qualifications into a single Qualifications section? The instruction says use headings like Qualifications, Skills, Benefits, Pay, Schedule. It lists Qualifications as a possible heading. So we could have a Qualifications section that includes both required and preferred. That would reduce number of sections. Similarly Skills could be separate but we have skills mentioned in qualifications (programming languages). Could incorporate into Qualifications. Thus we could have sections: About the role, Responsibilities, Qualifications, Benefits, Pay, Schedule. That's six sections. We need to ensure we don't include filler like "commensurate with experience". Not present. We need to remove boilerplate: EEO, equal-opportunity, scam-warning, application instructions, navigation, cookie, legal. The posting includes a lot of EEO statements at the end: "As a global business, we rely on the unique backgrounds..." etc. Also includes accommodation contact, fraud warning, etc. We must remove those. Also remove duplicated lines. We must preserve all substantive information. So we need to keep the benefits details, pay range, schedule details, etc. Now produce HTML fragment: no or , no markdown fences. We'll output something like:
About the role
Noetica is an AI-native legal technology company, now part of Thomson Reuters, that transforms complex corporate transaction data into structured, searchable market intelligence. Its platform helps legal and finance professionals analyze deal terms, identify market trends, and assess risk with greater speed and confidence. As a Staff Data Platform Engineer, you will set the technical direction for Noetica’s data infrastructure and lead the evolution of systems that process legal and financial document data at significant scale. This hands-on technical leadership role combines architecture, implementation, cross-functional influence, and team development to ensure the platform supports rapid AI innovation while meeting demanding reliability, security, and compliance standards.
Responsibilities
- Own the technical roadmap for the data platform, balancing scalability, reliability, security, compliance, and business priorities.
- Architect next-generation pipelines and storage systems for high-volume document data.
- Lead decisions on technology selection, system design, and infrastructure strategy across the platform.
- Advance data governance, privacy controls, compliance frameworks, and audit capabilities for regulated data.
- Partner with machine learning and AI leaders to enable model training, evaluation, and inference at scale.
- Establish technical standards, mentor engineers, and help build a high-performing platform organization.
- Represent the platform function in company-wide architecture and engineering decisions.
- Remain hands-on by owning critical systems and contributing code to solve complex technical challenges.
Qualifications
Required:
- Ten or more years of software engineering experience, including at least six years focused on data platforms, infrastructure, or large-scale backend systems.
- Demonstrated expertise architecting distributed systems, including high-throughput pipelines and petabyte-scale or similarly complex data processing environments.
- Deep knowledge of big data technologies, distributed databases, and modern data platforms.
- Strong systems programming skills in Python, Java, C++, Rust, or Go, with experience delivering production systems.
- Expertise in data compliance, privacy engineering, and secure data handling in regulated environments.
- Experience building and mentoring engineering teams and driving complex technical initiatives to completion.
- Sound judgment in balancing engineering quality, delivery speed, cost, risk, and business impact.
Preferred:
- Experience in a high-growth environment where platform infrastructure was critical to business success.
- A record of leading major architectural transitions or platform migrations.
- Published technical writing or public speaking on data systems, architecture, or engineering practices.
- Experience with machine learning infrastructure, feature stores, or platforms that support AI workloads.
- Background in legal technology, financial services, or another highly regulated industry.
- Coding in Python.
Benefits
- Hybrid Work Model: flexible hybrid working environment for office‑based roles while delivering a seamless experience that is digitally and physically connected.
- Flexibility & Work‑Life Balance: Flex My Way policies, work‑from‑anywhere for up to 8 weeks per year, supportive workplace policies to manage personal and professional responsibilities.
- Career Development and Growth: Grow My Way programming, skills‑first approach, continuous learning.
- Industry Competitive Benefits: comprehensive benefit plans including flexible vacation, two company‑wide Mental Health Days off, access to Headspace app, retirement savings, tuition reimbursement, employee incentive programs, resources for mental, physical, and financial wellbeing.
- Culture: globally recognized award‑winning reputation for inclusion, belonging, flexibility, work‑life balance.
- Social Impact: Social Impact Institute, two paid volunteer days off annually, pro‑bono consulting projects, ESG initiatives.
- Making a Real‑World Impact: helping customers pursue justice, truth, transparency; upholding rule of law, turning wheels of commerce, catching bad actors, reporting facts, providing trusted unbiased information worldwide.
- Thomson Reuters benefits: market‑competitive health, dental, vision, disability, life insurance; competitive 401k with company match; market‑leading work‑life benefits including vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave; optional hospital, accident and sickness insurance (employee‑paid); optional life and AD&D insurance (employee‑paid); Flexible Spending and Health Savings Accounts; fitness reimbursement; access to Employee Assistance Program; Group Legal Identity Theft Protection benefit (employee‑paid); access to 529 Plan; commuter benefits; Adoption & Surrogacy Assistance; Tuition Reimbursement; access to Employee Stock Purchase Plan.
Pay
The base compensation range for the role in any of the eligible locations (New York City, San Francisco, Los Angeles, Irvine, CA; McLean, VA; Washington, DC) is $146,800 USD – $272,600 USD. Base pay is positioned within the range based on knowledge, skills, experience and internal equity. The role may also be eligible for an Annual Bonus based on enterprise