Keyrus is a global consulting and technology company focused on making data matter — truly matter — from a human perspective.
Founded in 1996, Keyrus operates in 28+ countries across 5 continents, with more than 3,300 people worldwide. Our strength comes from combining deep expertise in Data & Analytics, AI, Digital, and Management Consulting with a strong understanding of business realities.
Data is never the goal in itself.
We use data to shape understanding, design meaningful experiences, and enable better, real-life decisions.
At Keyrus, we also believe companies have a responsibility beyond performance. Through our Foundation and ESG initiatives, we actively contribute to sustainability, inclusion, and positive societal impact.
#OneTeamOneKeyrus
As a Data Engineer (GCP), you will work at the intersection of data, technology, and business, helping our clients turn complexity into clarity and insights into impact.
You will be part of international, client-facing projects, contributing to the development of robust data pipelines and analytical platforms built on Google Cloud Platform.
📍 Job location: Remote - Portugal or Spain
🕒 Contract type: Permanent
🗓 Target start date: ASAP
⏰ Working hours: Full-time (40h/week)
Note: All applications (CVs) must be submitted in English.
In this role, you will:
Design, develop, and maintain scalable data pipelines on Google Cloud Platform
Work with large datasets using tools such as BigQuery and Dataflow
Build reliable data models that support analytics and business use cases
Collaborate with consultants, engineers, and client stakeholders in delivery teams
Contribute to best practices in data engineering and cloud-based architectures
You will work in complex, evolving client data environments
You are expected to balance scalability, performance, and delivery timelines
You will collaborate with multidisciplinary and multicultural teams
Client-facing contexts require both technical expertise and strong communication
Solid hands-on experience with Google Cloud Platform
Strong experience with BigQuery, Dataflow, or similar GCP services
Experience building scalable data pipelines and data models
Good understanding of data engineering best practices
Ability to interact confidently in client-facing environments
Strong problem-solving skills and collaborative mindset
Fluency in English
Must be a Portuguese or European citizen, or hold a valid work permit for Portugal or Spain
Experience in consulting environments
Exposure to international or multicultural projects
Knowledge of other cloud or data ecosystem tools
Knowledge of Portuguese and/or Spanish
At Keyrus, salary ranges reflect different levels of mastery and impact within the same role — not different job titles.
Bottom of the range
You meet the core requirements and will need ramp-up time and support.
Middle of the range
You are fully autonomous from Day 1 and deliver consistently.
Top of the range
You are a reference for the role, mentor others, and raise the bar for the team.
Final offers are based on experience, autonomy, scope, and market context, and are discussed transparently during the process.
Competitive salary aligned with your experience and the data market
Meal allowance: €10.20/day
Flexible benefits plan
Private medical insurance
22 days of annual leave, increasing every 3 years (up to 25 days)
Continuous learning via KLX – Keyrus Learning Experience
A collaborative, international, and human-centred work environment
Joining Keyrus means joining:
A market leader in Data Intelligence
A company where people, trust, and diversity are core values
An environment that values ownership, flexibility, and innovation
A place where different backgrounds and perspectives are not just welcomed = they are essential
We believe diversity drives better thinking, stronger teams, and better outcomes.
Everyone belongs at Keyrus.
We are committed to building an inclusive workplace and encourage applications from all backgrounds, regardless of race, ethnicity, gender identity, sexual orientation, age, disability, or any other protected characteristic.