Cloud AI Data Engineer II, Professional Services, Google Cloud
for section headings (About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)
2. Use - for lists,
for prose
3. Do NOT repeat job title as heading
4. Do NOT put Job ID/requisition numbers as headings
5. Preserve ALL substantive information
6. Remove boilerplate (cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions)
7. Include section ONLY when posting has real specific content - never emit heading followed by filler/placeholder text
8. Never create Pay/Schedule/Benefits sections unless posting actually states them
9. Prefer few substantive sections over many thin ones
10. Output ONLY HTML fragment - no /, no markdown code fences
Let me analyze the content:
The posting has:
- Application window info (Nov 3, 2026) - minor metadata, fold into
or drop
- Benefits package (detailed) - this is substantive, should include Benefits section
- Preferred working locations - minor metadata
- Minimum qualifications - this is Requirements/Qualifications
- Preferred qualifications - this is Preferred Qualifications
- About The Job - this is About the role
- Responsibilities - this is Responsibilities
- Pay info: "Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $156000 - $226000 (USD) + 15% bonus target + equity + benefits" - this is Pay section
- EEO boilerplate - remove
- Accommodation info - remove (boilerplate)
Sections to include:
1. About the role (from "About The Job")
2. Responsibilities (from "Responsibilities")
3. Requirements (from "Minimum qualifications")
4. Preferred qualifications (from "Preferred qualifications")
5. Benefits (detailed benefits listed)
6. Pay (salary range and bonus/equity info)
7. Schedule? There's travel up to 30% - could be Schedule or part of Responsibilities. The rules mention Schedule as a possible heading. Since travel is mentioned, I could include a Schedule section or fold into Responsibilities. The rules say "Schedule" is a possible heading. I'll include a brief Schedule section for travel requirement.
Let me structure:
About the role
...content from About The Job...
Responsibilities
- ...
Requirements
- ...
Preferred qualifications
- ...
Benefits
- ...
Pay
...
Schedule
Travel up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities.
Wait, the travel is mentioned in Responsibilities section: "Travel regularly up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities." That's part of responsibilities. But also "Communicate effectively via video conferencing..." is a responsibility. I'll keep travel in Responsibilities list, but also could have Schedule section. The rules say "Schedule" as possible heading. Since travel is a schedule-related item, I'll include a Schedule section.
But the rules: "never create Pay/Schedule/Benefits sections unless the posting actually states them." The posting states travel requirement, so Schedule is stated. Benefits are stated. Pay is stated. So all three are valid.
Now, the application window info: "The application window will be open until at least November 3rd, 2026. This opportunity will remain online based on business needs which may be before or after the specified date." This is minor metadata, fold into a short or drop. I'll drop it as it's not substantive.
Preferred working locations: "Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Austin, TX, USA; Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA; Seattle, WA, USA." This is minor metadata, could fold into a
in About the role or drop. I'll include as a note in About the role.
Now, let's extract content.
About The Job:
"The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners. As an AI Data Engineer, you will guide customers on how to ingest, store, process, analyze, explore, and visualize data on Google Cloud Platform. You will lead data migrations and transformations, partner with clients to architect scalable data processing systems, build efficient data pipelines, and resolve platform challenges. In this role, you will collaborate with Google's strategic cloud customers and our team to successfully implement Google Cloud products. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems."
That's a lot of prose. I'll put as
paragraphs.
Responsibilities:
- Act as a trusted technical advisor to customers and solve complex Big Data challenges.
- Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders.
- Analyze on-premises and cloud database environments and consult on the optimal design for performance and deployment on Google Cloud Platform.
- Travel regularly up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities.
- Communicate effectively via video conferencing for meetings, technical reviews, and onsite delivery activities.
Minimum qualifications:
- Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
- 5 years of experience with data processing software (e.g., Spark, Beam) and algorithms.
- Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams.
- Experience with database administration techniques or data engineering, as well as writing software in Java, Python, or SQL.
Preferred qualifications:
- Google Cloud Platform (GCP) Professional Data Engineer Certification.
- Experience in technical consulting.
- Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.
- Experience working with Big Data, information retrieval, data mining, or machine learning.
- Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.
- Experience building machine learning solutions and working with technical customers.
Benefits:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Pay:
"Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $156000 - $226000 (USD) + 15% bonus target + equity + benefits"
Schedule: Travel up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities. (Already in responsibilities, but I'll include a Schedule section for clarity.)
Now, I need to output HTML fragment.
I'll write:
About the role
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.
As an AI Data Engineer, you will guide customers on how to ingest, store, process, analyze, explore, and visualize data on Google Cloud Platform. You will lead data migrations and transformations, partner with clients to architect scalable data processing systems, build efficient data pipelines, and resolve platform challenges. In this role, you will collaborate with Google's strategic cloud customers and our team to successfully implement Google Cloud products.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Preferred working locations: Austin, TX; Atlanta, GA; Boulder, CO; Chicago, IL; Seattle, WA.
Responsibilities
- Act as a trusted technical advisor to customers and solve complex Big Data challenges.
- Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders.
- Analyze on-premises and cloud database environments and consult on the optimal design for performance and deployment on Google Cloud Platform.
- Travel regularly up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities.
- Communicate effectively via video conferencing for meetings, technical reviews, and onsite delivery activities.
Requirements
- Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
- 5 years of experience with data processing software (e.g., Spark, Beam) and algorithms.
- Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams.
- Experience with database administration techniques or data engineering, as well as writing software in Java, Python, or SQL.
Preferred qualifications
- Google Cloud Platform (GCP) Professional Data Engineer Certification.
- Experience in technical consulting.
- Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.
- Experience working with Big Data, information retrieval, data mining, or machine learning.
- Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.
- Experience building machine learning solutions and working with technical customers.
Benefits
- Health, dental, vision, life, and disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
for prose 3. Do NOT repeat job title as heading 4. Do NOT put Job ID/requisition numbers as headings 5. Preserve ALL substantive information 6. Remove boilerplate (cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions) 7. Include section ONLY when posting has real specific content - never emit heading followed by filler/placeholder text 8. Never create Pay/Schedule/Benefits sections unless posting actually states them 9. Prefer few substantive sections over many thin ones 10. Output ONLY HTML fragment - no /, no markdown code fences Let me analyze the content: The posting has: - Application window info (Nov 3, 2026) - minor metadata, fold into
or drop - Benefits package (detailed) - this is substantive, should include Benefits section - Preferred working locations - minor metadata - Minimum qualifications - this is Requirements/Qualifications - Preferred qualifications - this is Preferred Qualifications - About The Job - this is About the role - Responsibilities - this is Responsibilities - Pay info: "Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $156000 - $226000 (USD) + 15% bonus target + equity + benefits" - this is Pay section - EEO boilerplate - remove - Accommodation info - remove (boilerplate) Sections to include: 1. About the role (from "About The Job") 2. Responsibilities (from "Responsibilities") 3. Requirements (from "Minimum qualifications") 4. Preferred qualifications (from "Preferred qualifications") 5. Benefits (detailed benefits listed) 6. Pay (salary range and bonus/equity info) 7. Schedule? There's travel up to 30% - could be Schedule or part of Responsibilities. The rules mention Schedule as a possible heading. Since travel is mentioned, I could include a Schedule section or fold into Responsibilities. The rules say "Schedule" is a possible heading. I'll include a brief Schedule section for travel requirement. Let me structure:
About the role
...content from About The Job...
Responsibilities
- ...
Requirements
- ...
Preferred qualifications
- ...
Benefits
- ...
Pay
...
Schedule
Travel up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities.
Wait, the travel is mentioned in Responsibilities section: "Travel regularly up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities." That's part of responsibilities. But also "Communicate effectively via video conferencing..." is a responsibility. I'll keep travel in Responsibilities list, but also could have Schedule section. The rules say "Schedule" as possible heading. Since travel is a schedule-related item, I'll include a Schedule section. But the rules: "never create Pay/Schedule/Benefits sections unless the posting actually states them." The posting states travel requirement, so Schedule is stated. Benefits are stated. Pay is stated. So all three are valid. Now, the application window info: "The application window will be open until at least November 3rd, 2026. This opportunity will remain online based on business needs which may be before or after the specified date." This is minor metadata, fold into a shortor drop. I'll drop it as it's not substantive. Preferred working locations: "Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Austin, TX, USA; Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA; Seattle, WA, USA." This is minor metadata, could fold into a
in About the role or drop. I'll include as a note in About the role. Now, let's extract content. About The Job: "The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners. As an AI Data Engineer, you will guide customers on how to ingest, store, process, analyze, explore, and visualize data on Google Cloud Platform. You will lead data migrations and transformations, partner with clients to architect scalable data processing systems, build efficient data pipelines, and resolve platform challenges. In this role, you will collaborate with Google's strategic cloud customers and our team to successfully implement Google Cloud products. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems." That's a lot of prose. I'll put as
paragraphs. Responsibilities: - Act as a trusted technical advisor to customers and solve complex Big Data challenges. - Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders. - Analyze on-premises and cloud database environments and consult on the optimal design for performance and deployment on Google Cloud Platform. - Travel regularly up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities. - Communicate effectively via video conferencing for meetings, technical reviews, and onsite delivery activities. Minimum qualifications: - Bachelor's degree in Computer Science, a related field, or equivalent practical experience. - 5 years of experience with data processing software (e.g., Spark, Beam) and algorithms. - Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams. - Experience with database administration techniques or data engineering, as well as writing software in Java, Python, or SQL. Preferred qualifications: - Google Cloud Platform (GCP) Professional Data Engineer Certification. - Experience in technical consulting. - Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments. - Experience working with Big Data, information retrieval, data mining, or machine learning. - Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments. - Experience building machine learning solutions and working with technical customers. Benefits: - Health, dental, vision, life, disability insurance - Retirement Benefits: 401(k) with company match - Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment - Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) - Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks - Baby Bonding Leave: 18 weeks - Holidays: 13 paid days per year Pay: "Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $156000 - $226000 (USD) + 15% bonus target + equity + benefits" Schedule: Travel up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities. (Already in responsibilities, but I'll include a Schedule section for clarity.) Now, I need to output HTML fragment. I'll write:
About the role
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.
As an AI Data Engineer, you will guide customers on how to ingest, store, process, analyze, explore, and visualize data on Google Cloud Platform. You will lead data migrations and transformations, partner with clients to architect scalable data processing systems, build efficient data pipelines, and resolve platform challenges. In this role, you will collaborate with Google's strategic cloud customers and our team to successfully implement Google Cloud products.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Preferred working locations: Austin, TX; Atlanta, GA; Boulder, CO; Chicago, IL; Seattle, WA.
Responsibilities
- Act as a trusted technical advisor to customers and solve complex Big Data challenges.
- Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders.
- Analyze on-premises and cloud database environments and consult on the optimal design for performance and deployment on Google Cloud Platform.
- Travel regularly up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities.
- Communicate effectively via video conferencing for meetings, technical reviews, and onsite delivery activities.
Requirements
- Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
- 5 years of experience with data processing software (e.g., Spark, Beam) and algorithms.
- Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams.
- Experience with database administration techniques or data engineering, as well as writing software in Java, Python, or SQL.
Preferred qualifications
- Google Cloud Platform (GCP) Professional Data Engineer Certification.
- Experience in technical consulting.
- Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.
- Experience working with Big Data, information retrieval, data mining, or machine learning.
- Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.
- Experience building machine learning solutions and working with technical customers.
Benefits
- Health, dental, vision, life, and disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment