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Google Cloud in Buenos Aires, Argentina is seeking a Data Customer Solutions Engineer to design, deploy and manage scalable databases on Google Cloud. You will work with customers and partners to migrate data, model governance, and deliver workshops that promote best practices in database design and operations.
The role requires strong SQL, Java/C++/Python, and experience with MySQL, PostgreSQL, Oracle, and NoSQL like MongoDB, plus data modeling and cloud data services such as Spanner, BigTable
Data Customer Solutions Engineer, Google Cloud
Share Data Customer Solutions Engineer, Google Cloud
_corporate_fare_ Google _place_ Buenos Aires, Argentina; Mexico City, CDMX, Mexico
**Early**
Experience completing work as directed, and collaborating with teammates; developing knowledge of relevant concepts and processes.
Share Data Customer Solutions Engineer, Google Cloud
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XIn most instances, this position requires in-person interviews as part of the hiring process.
Please submit your resume in English - we can only consider applications submitted in this language.
Only applications of candidates with Mexican citizenship will be evaluated for this role in compliance with the provisions of Article 7 of the Federal Labor Law.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: **Buenos Aires, Argentina; Mexico City, CDMX, Mexico** .
**Minimum qualifications:**
+ Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience.
+ Experience coding with one or more programming languages (e.g., Java, C/C++, Python).
+ Experience in developing and troubleshooting applications with popular database management systems such as MySQL, PostgreSQL, Oracle, and NoSQL databases like MongoDB
+ Experience with Structured Query Language (SQL).
**Preferred qualifications:**
+ Bachelor's degree with 5 years of technical troubleshooting.
+ Proficiency in data modeling, distributed systems, and SQL, NoSQL, and Google Cloud databases (Spanner, BigTable, AlloyDB).
+ Expertise in designing and executing large-scale data migrations from on-premise systems to the cloud.
+ Strong programming skills (Python, Java), script automation, and DevOps implementation using CI/CD and IaC tools.
+ Deep understanding of data protection, encryption techniques (KMS, HSMs), and regulatory compliance (GDPR, CCPA, HIPAA).
+ Ability to communicate in English and Portuguese/Spanish fluently for LATAM stakeholders.
**About the job**
As a Strategic Cloud Data Engineer, you will work with customers and partner teams to design,develop,deploy and manage highly scalable and reliable databases on the Google Cloud Platform meeting the Organization's storage demands. You will work on data migrations and modernization projects incorporating best practices of data governance and security controls. You will travel to customer sites to deploy solutions and deliver workshops to educate and empower customer teams to adhere to best practices in Database design and operations. Additionally, you will work closely with Product Management and Product Engineering teams to build and constantly drive excellence in our products that solve the biggest customer challenges.
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.
**Responsibilities**
+ Interact with stakeholders to translate complex business and technical requirements into recommendations for scalable and cost-effective database solutions and advisory services.
+ Engage with technical leads and partners to lead high velocity data migration and modernisation to Google Cloud Platform (GCP) using Google or third-party tools and services.
+ Develop and implement data quality and governance procedures to ensure the accuracy and reliability of data.
+ Work with customer or partner teams to troubleshoot their complex storage systems for potential performance challenges.
+ Take various project requirements and organize them into clear goals and objectives, and create a work breakdown structure to manage internal and external stakeholders.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See alsoGoogle's EEO Policy ( ,Know your rights: workplace discrimination is illegal ( ,Belonging at Google ( , andHow we hire ( .
If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form ( .
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also and If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form:
Functional Responsibilities - Data Engineering
Ensure governance, risk, and audit compliance for in-country operations
Deliver measurable outcomes: data SLO attainment, improved data quality metrics, faster access to network data, and demonstrable downstream gains in automation, reliability, and analytics
Mission As the Data Engineer you will design, build, and optimize scalable data infrastructure that powers marketing, business intelligence, and strategic decision-making across the organization.
You will develop reliable data pipelines, integrate third-party platforms, and transform raw data into actionable insights through automation, analytics, and visualization.
Working closely with cross-functional teams, you will ensure data is accurate, accessible, and optimized for performance while continuously identifying opportunities to improve processes and capabilities.
This role combines technical expertise, innovation, and collaboration to deliver high-quality data solutions that support business growth.
Outcomes Data Pipeline Development – Design, build, and optimize end-to-end data pipelines from ingestion through transformation and visualization, delivering scalable, reliable solutions that achieve 99%+ successful pipeline execution.
Platform Integrations – Integrate third-party tools and platforms, including CRM…
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We are looking for a Mid-level Data Engineer to build and maintain dbt pipelines and Snowflake data marts behind customer-facing reporting, spend analytics, and AI features.
- Build and maintain the dbt pipelines, data marts, and warehouse models that serve in-app reporting, spend analytics, AI features, and internal analytics, treating them as production systems.
- 3+ years in analytics engineering, data engineering, or a closely related role, including hands-on work on production data pipelines that other systems or customers depended on.
- Experience building or maintaining API services on top of warehouse data (FastAPI or similar).
- Professional growth : Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation : USD-based pay with education, fitness, and team activity budgets.
- Exciting projects : Modern solutions with Fortune 500 and top product companies.
- Flextime : Flexible schedule with remote and office options.
We have an exciting and rewarding opportunity for you to take your data engineering career to the next level.
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