📍 Job Overview

Job Title: Customer Engineer, Data Analytics, Google Cloud
Company: Google
Location: Medellín, Antioquia, Colombia
Job Type: On-site
Category: Data Analytics, Cloud Infrastructure
Date Posted: June 13, 2025
Experience Level: 5-10 years
Remote Status: On-site

🚀 Role Summary

📝 Enhancement Note: This role requires a strong background in cloud native architecture and data analytics to serve as a technical expert for Google Cloud customers. The ideal candidate will have a deep understanding of Big Data technologies and experience in technical sales or consulting.

💻 Primary Responsibilities

📝 Enhancement Note: The primary responsibilities of this role revolve around customer engagement, technical problem-solving, and solution architecture using Google Cloud products.
Collaborate with the team to identify and qualify business opportunities, understanding customer objections and developing strategies to resolve technical blockers related to the data life-cycle.
Share in-depth data analytics experience to support the technical relationship with customers, including technology advocacy, bid responses, product and solution briefings, proof-of-concept work, and partnering with product management to prioritize solutions impacting customer adoption to Google Cloud.
Identify business and technical requirements, conduct full technical discovery, and architect client solutions to meet gathered requirements.
Work directly with Google Cloud products to demonstrate and prototype integrations in customer and partner environments.
Prepare and deliver business messaging to highlight the Google Cloud value proposition using techniques such as whiteboard and slide presentations, product demonstrations, white papers, and RFI responses.

🎓 Skills & Qualifications

Education: A Bachelor's degree or equivalent practical experience in a relevant field such as Computer Science, Data Science, or a related discipline.

Experience: 6+ years of experience with cloud native architecture in a customer-facing or support role, with a focus on Big Data technologies and data analytics.

Required Skills:

Proven experience with cloud native architecture and Big Data technologies or concepts, such as analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, NoSQL, performance or scalability optimizations, or batch versus streaming.
Experience with architecture design, implementing, tuning, schema design, and query optimization of scalable and distributed systems.
Strong understanding of customer requirements and the ability to break down requirements and design technical architectures.
Excellent communication, presentation, and organizational skills.

Preferred Skills:

Experience in technical sales or consulting in cloud computing, data analytics, or Big Data.
Experience with developing data warehousing, data lakes, batch/real-time event processing, streaming, data processing (ETL/ELT), data migrations, data visualization tools, and data governance on cloud native architectures.
Experience with aspects of cloud computing (e.g., infrastructure, storage, platforms, and data), as well as the cloud market, engaged dynamics, and customer buying behavior.

📊 Web Portfolio & Project Requirements

📝 Enhancement Note: As this role focuses on data analytics and cloud infrastructure, a strong portfolio demonstrating experience with Big Data technologies, data warehousing, and cloud architecture is essential.

Portfolio Essentials:

Case studies demonstrating successful data analytics projects, including data warehousing, data lakes, ETL/ELT processes, and data governance.
Examples of architecture design, implementation, and optimization of scalable and distributed systems.
Proof of experience with cloud native architecture and customer-facing roles.

Technical Documentation:

Code samples and documentation showcasing proficiency in SQL, NoSQL, and other relevant programming languages.
Detailed project reports or whitepapers demonstrating data analytics expertise and technical problem-solving skills.

💵 Compensation & Benefits

Salary Range: COP 15,000,000 - COP 20,000,000 per year (Based on market research for data analytics roles in Medellín, Colombia, with 6-10 years of experience)

Benefits:

Competitive salary and benefits package, including health insurance, retirement plans, and paid time off.
Opportunities for professional development, including training, workshops, and conference attendance.
A dynamic and collaborative work environment with a focus on innovation and continuous learning.

Working Hours: Full-time, Monday - Friday, with occasional overtime as needed to support customer projects and deadlines.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology, with a focus on cloud computing and data analytics.

Company Size: Large (Over 100,000 employees), with a global presence and a strong commitment to diversity, equity, and inclusion.

Founded: 1998, with a rich history of innovation and industry leadership in search, advertising, and cloud technologies.

Team Structure:

Collaborative, cross-functional teams working on various aspects of Google Cloud, including data analytics, infrastructure, and platform development.
Flat hierarchy, with a focus on empowerment and decision-making at the team level.

Development Methodology:

Agile development processes, with a focus on continuous integration, delivery, and improvement.
Regular code reviews, testing, and quality assurance practices to ensure high-quality products and solutions.
Deployment strategies that prioritize scalability, reliability, and performance.

Company Website: Google Cloud

📈 Career & Growth Analysis

Web Technology Career Level: Senior Customer Engineer, with a focus on data analytics and cloud infrastructure. This role requires a high level of technical expertise and experience, as well as strong communication and presentation skills.

Reporting Structure: The Customer Engineer will report directly to the Technical Lead or Manager within the Google Cloud team, collaborating with various stakeholders, including product managers, engineers, and sales teams.

Technical Impact: This role has a significant impact on Google Cloud's customer success and growth, as the Customer Engineer will be responsible for understanding customer requirements, designing technical architectures, and driving adoption of Google Cloud products and services.

Growth Opportunities:

Technical leadership roles within Google Cloud, focusing on data analytics, cloud architecture, or product management.
Opportunities to specialize in emerging technologies and trends within the data analytics and cloud computing domains.
Potential to work on high-impact projects and initiatives, driving innovation and industry standards within Google Cloud.

🌐 Work Environment

Office Type: Modern, collaborative workspaces designed to facilitate innovation, creativity, and teamwork.

Office Location(s): Medellín, Antioquia, Colombia, with opportunities for regional travel to support customer projects and initiatives.

Workspace Context:

Access to cutting-edge technology, tools, and resources to support data analytics and cloud infrastructure projects.
Collaborative workspaces, including meeting rooms, brainstorming areas, and quiet spaces for focused work.
Opportunities for cross-functional collaboration with designers, marketers, and other stakeholders within Google Cloud.

Work Schedule: Full-time, with a flexible work schedule that accommodates customer needs and project deadlines. Occasional overtime may be required to support critical customer projects and initiatives.

📄 Application & Technical Interview Process

Interview Process:

Technical Assessment: A hands-on assessment focusing on data analytics, cloud architecture, and problem-solving skills using Google Cloud products and services.
Behavioral Interview: A discussion-based interview focusing on customer-facing experience, communication skills, and cultural fit within Google Cloud.
Architecture Design Challenge: A case study or project-based challenge that requires the candidate to design a technical architecture for a hypothetical customer scenario using Google Cloud products and services.
Final Review: A review of the candidate's overall fit for the role, considering technical skills, customer-facing experience, and cultural alignment with Google Cloud.

Portfolio Review Tips:

Highlight successful data analytics projects and cloud architecture case studies, demonstrating problem-solving skills, technical expertise, and customer impact.
Include examples of code samples, documentation, and technical reports that showcase proficiency in relevant programming languages, tools, and technologies.
Prepare a live demo or presentation showcasing the candidate's ability to communicate complex technical concepts effectively.

Technical Challenge Preparation:

Brush up on data analytics concepts, cloud architecture principles, and Google Cloud products and services.
Practice problem-solving skills and architecture design exercises using relevant tools and resources.
Familiarize oneself with Google Cloud's development methodologies, deployment strategies, and best practices.

ATS Keywords: (Organized by category)

Programming Languages: Python, SQL, NoSQL, Java, C++
Cloud Platforms: Google Cloud, AWS, Azure, GCP
Data Analytics Tools: BigQuery, Cloud Dataflow, Cloud Pub/Sub, Cloud DataProc, Cloud Composer, Looker
Cloud Infrastructure: Compute Engine, App Engine, Kubernetes Engine, Cloud Functions, Cloud Run, Cloud Storage
Databases: Cloud SQL, Cloud Spanner, Firestore, Bigtable, Memorystore, Cloud Datastore
Methodologies: Agile, Scrum, Kanban, DevOps, CI/CD
Soft Skills: Communication, Presentation, Problem-solving, Customer-facing, Technical Sales, Consulting
Industry Terms: Data Warehousing, Data Lakes, ETL, ELT, Data Governance, Data Migrations, Batch Processing, Streaming, Scalability, Performance Optimization

🛠 Technology Stack & Web Infrastructure

Cloud Platforms:

Google Cloud Platform (GCP)
Amazon Web Services (AWS)
Microsoft Azure

Data Analytics Tools:

BigQuery
Cloud Dataflow
Cloud Pub/Sub
Cloud DataProc
Cloud Composer
Looker

Cloud Infrastructure:

Compute Engine
App Engine
Kubernetes Engine
Cloud Functions
Cloud Run
Cloud Storage

Databases:

Cloud SQL
Cloud Spanner
Firestore
Bigtable
Memorystore
Cloud Datastore

Programming Languages:

Python
SQL
NoSQL
Java
C++

Methodologies:

Agile
Scrum
Kanban
DevOps
CI/CD

Soft Skills:

Communication
Presentation
Problem-solving
Customer-facing
Technical Sales
Consulting

Industry Terms:

Data Warehousing
Data Lakes
ETL
ELT
Data Governance
Data Migrations
Batch Processing
Streaming
Scalability
Performance Optimization

👥 Team Culture & Values

Web Development Values:

User-centric: Focus on understanding and addressing customer needs and pain points.
Innovation: Embrace continuous learning and experimentation to drive industry-leading solutions.
Collaboration: Foster a culture of teamwork, knowledge-sharing, and cross-functional collaboration.
Quality: Prioritize high-quality products, solutions, and customer experiences.

Collaboration Style:

Cross-functional integration: Collaborate with designers, marketers, and other stakeholders to ensure customer-centric solutions.
Code review culture: Encourage peer-to-peer learning, feedback, and continuous improvement.
Knowledge sharing: Promote a culture of mentorship, workshops, and training to support professional growth and development.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Data Warehousing & Data Lakes: Design, implement, and optimize data warehousing and data lakes solutions using Google Cloud products and services.
ETL/ELT Processes: Develop, optimize, and manage ETL/ELT processes to ensure data accuracy, consistency, and timeliness.
Data Governance: Implement and enforce data governance policies and procedures to ensure data quality, security, and compliance.
Cloud Architecture: Design, implement, and optimize scalable and distributed systems using Google Cloud products and services.

Learning & Development Opportunities:

Technical Skills Development: Pursue certifications, workshops, and training opportunities to enhance expertise in data analytics, cloud architecture, and Google Cloud products and services.
Conference Attendance: Attend industry conferences, webinars, and events to stay up-to-date with the latest trends and best practices in data analytics and cloud computing.
Technical Mentorship: Seek mentorship opportunities from experienced team members to gain insights into architecture design, optimization, and problem-solving.

💡 Interview Preparation

Technical Questions:

Data Analytics: Prepare for questions related to data warehousing, data lakes, ETL/ELT processes, data governance, and data migrations using Google Cloud products and services.
Cloud Architecture: Brush up on cloud architecture principles, scalability, performance optimization, and deployment strategies using Google Cloud Platform (GCP), AWS, and Azure.
Problem-solving: Practice problem-solving exercises and architecture design challenges using relevant tools and resources.

Company & Culture Questions:

Google Cloud: Research Google Cloud's mission, values, and commitment to innovation and customer success.
Data Analytics: Prepare for questions related to data analytics trends, best practices, and industry standards using Google Cloud products and services.
Customer Impact: Demonstrate an understanding of Google Cloud's customer-centric approach and the importance of driving customer success and adoption.

Portfolio Presentation Strategy:

Live Demo: Prepare a live demo or presentation showcasing successful data analytics projects and cloud architecture case studies using Google Cloud products and services.
Code Walkthrough: Include code samples and technical documentation that demonstrate proficiency in relevant programming languages, tools, and technologies.
Architecture Design: Prepare a detailed architecture design for a hypothetical customer scenario, highlighting the candidate's ability to design scalable, distributed, and optimized solutions using Google Cloud products and services.

📌 Application Steps

To apply for this Customer Engineer, Data Analytics, Google Cloud position:

Submit your application through the Google Careers website.
Customize your resume and portfolio to highlight relevant data analytics, cloud architecture, and customer-facing experience.
Prepare for technical assessments, behavioral interviews, and architecture design challenges using Google Cloud products and services.
Research Google Cloud's mission, values, and commitment to innovation and customer success to demonstrate cultural fit and alignment with the organization's goals.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and data analytics industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Customer Engineer, Data Analytics, Google Cloud