Data Customer Solutions Engineer, Google Cloud
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
_info_outline_
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.
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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.
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Key Responsibilities
Functional Responsibilities - Data Engineering
Regional Responsibilities - Argentina IP Foundational Services Site Lead
Ensure governance, risk,



and audit compliance for in-country operations
Define and execute the network data strategy, covering data modelling, authoritative sources, distribution, and how data is made available to consuming platforms
Build and operate the data platform: ingestion and streaming pipelines, transformation, storage and modelling, and performant serving APIs and self-service access for engineering teams
Establish consistent data models and identity standards for network entities (device, circuit, site, interface) so data can be reliably joined and reused across systems
Drive data quality as an engineering discipline: validation, automated testing, monitoring, and measurable quality targets across the data lifecycle
stablish data contracts and data SLOs covering freshness, completeness, accuracy, and availability, with clear ownership, versioning, and schema-evolution standards
Implement lineage and observability across data pipelines so issues can be traced to source and change impact can be assessed ahead of time
Partner with firm-wide data governance and data quality programmes to meet audit, risk, and regulatory obligations
Make network data AI-ready: structured, well-described, and accessible so agentic and LLM-driven capabilities can reason over accurate state, and apply AI within the data lifecycle itself
Establish engineering standards, testing frameworks, and CI/CD pipelines so data pipelines and services are production-grade, secure-by-design, and observable
Deliver measurable outcomes: data SLO attainment, improved data quality metrics, faster access to network data, and demonstrable downstream gains in automation, reliability, and analytics
Required Qualifications, Capabilities, and Skills
10+ years in data engineering or data platform engineering, including leadership roles running data systems at scale and manager-of-managers experience
Proven ownership of a production data platform: pipelines, modelling, storage, and serving, with accountability for freshness, correctness, and availability
Demonstrated experience establishing data governance in practice: ownership models, data contracts, data quality measurement, lineage, and schema evolution
Strong hands-on engineering foundation (Python, SQL, APIs, streaming and batch pipelines, modern data stores) and the judgment to hold a high engineering bar
Proven track record adopting agentic AI and LLM-driven capability in production engineering environments, and preparing data estates for AI consumption
Experience operating within formal risk and control frameworks: audit engagement, evidence quality standards, and remediation governance
Proven ability to scale teams and drive adoption of common data standards across partner teams
Strong integral collaboration skills across distributed, matrixed organizations
Prior site, country, or regional engineering hub leadership experience
Preferred Qualifications, Capabilities, and Skills
Infrastructure or network domain experience: inventory, topology, configuration, and telemetry data.
A strong plus, not a gate
Experience with source-of-truth platforms, or graph and topology data models
Experience with streaming telemetry and time-series data at scale
Financial services or other regulated environment experience
Experience supporting automation and reliability engineering teams as primary data consumers
Demonstrated use of AI to redesign data engineering workflows for measurable impact, and to build organizational AI fluency
Demonstrated experience in incident, problem, and change governance, including executive communications during high-severity events
Team Scope
Direct Org: 25 engineers (network data engineering), globally distributed
Growth aligned to the Network Services data platform build-out
Partnership: strong partnership with the automation platform and SRE teams, global Product Engineering, firm-wide data governance and data quality programmes, and regional Infrastructure leadership
Regional (matrix): site leadership for all IP Foundational Services engineers in Argentina
Buenos Aires, Buenos Aires, Argentina
Full time
R
Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.
Job Description
**GBS Chevron Global Business Services (GBS), located in Buenos Aires (Puerto Madero), Argentina, is accepting applications for the position of Data Engineer.
Successful candidates will join the IT Organization, which is part of a multifunction service and technical center with a workforce of more than **** employees that deliver business services and solutions to the corporation across the globe.
**
Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.
Responsibilities include:
+ Understand business use of data and stakeholder requirements to support work processes and strategic business objectives
+ Leverage data, software engineering, and data science techniques to create business value through data accessibility.
Includes data ingestion, data preparation and analytics processing.
+ Identify, acquire, cleanse & prepare, store data and develop data products aligned with defined architecture patterns
+ Responsible for normalizing and ingesting data from multiple sources.
+ Enable data scientists, making data available for advanced analytics models, and contributing to models.
+ Work with ML Engineer to scale and deploy solution including model, documentation, training, integration
+ Contributing to the inner source development of foundational tools, and/or the deployment of technical services.
Required Qualifications:
+ BS in Computer Science, Management Information Systems, Computer Engineer or related fields or equivalent experience.
+ +5 years in Data Engineer Role
+ Knowledge and/or experience with: data acquisition, preparation and validation; data movement and transformation; analytics solution architecture; big data computing; cloud computing,



core data architecture; information security technologies and software engineering using technologies such as: Azure Data Factory (ETL), Databricks, DevOps, CI/CD Pipeline Deployment, Python, Java, Ansible, Azure SQL, Azure Synapse, GIT, ADO, Azure Data Lake, Azure Analysis Services, Logic Apps, Microsoft Data Flows, Kimball Data Warehousing Methodology
+ Analytical thinking, Consulting, Critical Thinking
**Relocation Options:**
Relocation **may be** considered.
**International Considerations:**
Expatriate assignments **will not be** considered
**Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position**
Chevron participates in E-Verify in certain locations as required by law.
Chevron Corporation is one of the world's leading integrated energy companies.
Through its subsidiaries that conduct business worldwide, the company is involved in virtually every facet of the energy industry.
Chevron explores for, produces and transports crude oil and natural gas; refines, markets and distributes transportation fuels and lubricants; manufactures and sells petrochemicals and additives; generates power; and develops and deploys technologies that enhance business value in every aspect of the company's operations.
Chevron is based in Houston, Texas.
More information about Chevron is available at .
Chevron is an Equal Opportunity / Aff...
We do this by finding value-add and opportunistic investments offering solid returns to our investors.
Providing an opportunity to grow for our partners and creating lasting wealth for everyone with whom we conduct business is how we make our greatest contribution.
We specifically focus on self-storage projects capitalizing on amazing deals in other asset classes.
In ****, we were listed as the 5th fastest growing real estate company in the US and joined the list of the top 100 owners of self-storage.
We are members of the Inc.
**** fastest-growing private companies in America and in **** we were #13 in Denver Business Journals list of top places to work.
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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As always, message and data rates may apply ...
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WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
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.
WHAT YOU WILL DO
- 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.
MUST HAVES
-
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.
NICE TO HAVES
- Experience building or maintaining API services on top of warehouse data (FastAPI or similar).
PERKS AND BENEFITS
-
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.
Job responsibilities
Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
Collaborates with software engineers and teams to design, develop, test, and implement availability, reliability, scalability, and solutions in their applications
Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way.
Supports review of controls to ensure sufficient protection of enterprise data
Contributes to data and software engineering communities of practice and events that explore new and emerging technologies
Required qualifications, capabilities, and skills
Formal training or relevant data engineering certification and 5+ years applied experience
Experience in Qlik Sense in both ETL and Dashboard development
In depth knowledge of Qliksense scripting, QVD Files, Set Analysis
Practical experience in full stack projects, hands-on mainly with backend technologies such as Java, Spring Boot, JPA (Java Persistence API) Spring Data Repositories
Experience in developing, debugging, and maintaining code in a corporate ecosystem with one or more modern programming languages and database querying languages
Exposure to agile methodologies such as CI/CD, Application Resiliency, and Cybersecurity best practices
Experience with SQL relational DB technologies such as MySQL, Oracle RDMS.
Preferred qualifications, capabilities, and skills
Knowledge of Web Frameworks (. React) will be an added advantage.
Exposure to public cloud technologies, AWS/GCP/Azure experience or certifications is a plus
Experience in observability, monitoring, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, and others.
Familiarity with industry-wide technology trends and best practices
LangChain.
LangGraph.
AWS.
Argentina Full-time
#J-*****-Ljbffr

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