CloudPaySenior Data Engineer
About this job opportunity
Our Vision
To be the world's most trusted global payroll partner, simplifying pay for all employees.
Our Mission
Empowering global workforces with seamless, compliant, and innovative payroll and payment solutions, enabling businesses to thrive in a connected world.
Our People
Our fundamental beliefs at CloudPay are built on core values of professionalism, passion, empowerment, innovation, and teamwork. We value our employees and strive to create a great workplace where everyone is valued, heard, inspired, and encouraged to bring their authentic selves to work. We're committed to providing an excellent employee experience through fulfilling projects, empowerment to make a difference, and an environment that inspires innovation.
What makes this role exciting
This role is part of a new team responsible for building CloudPay’s new modern data platform.
We’re looking for a motivated and impact-driven Data Engineer to join our Data team. You will strengthen our data platform by designing and maintaining infrastructure and tooling that empower teams to build their own analytics, reports, and data products. You will also support the delivery of reliable, production-ready datasets that power analytics and AI/ML initiatives across CloudPay, including enabling AI/ML experimentation, training pipelines, and deploying models in production, with a focus on enhancing payroll and HR solutions.
You will be joining a newly created Data Engineering team with the mandate to build CloudPay’s modern data platform from scratch. This is a rare opportunity to influence architectural decisions, define engineering standards, and shape a platform that will power analytics, AI/ML initiatives, and next‑generation payroll and HR products at global scale.
If you’re passionate about data, thrive at the intersection of innovation and want to build a platform that powers data-driven and AI-first solutions at global scale, this role is for you.
Main responsibilities
Build and Maintain Pipelines: Design, develop, and optimize end-to-end data pipelines (real-time and batch) to support ML model training, inference, and analytics in a fast-paced, production environment.
Data Infrastructure & Platform Evolution: Build and evolve scalable data infrastructure that empowers teams to autonomously build and run pipelines, AI/ML models, and data products.
Support AI/ML Initiatives: Collaborate with Data Scientists and ML Engineers to operationalize machine learning and generative AI solutions, including model training, deployment, and monitoring.
Optimize Data Storage & Access: Design and maintain data storage and access patterns for high performance, scalability, and reliability.
Ensure Data Quality & Security: Implement governance, monitoring, and best practices to maintain accurate, performant, and compliant systems.
Deploy & Manage Model Serving Systems: Ensure seamless integration of models into production environments and maintain robust monitoring and performance tracking.
Collaborate & Enable: Partner with Product, Analytics, ML, and Engineering teams to provide structured datasets, enabling insights, predictive analytics, and AI-powered features.
Innovate & Experiment: Explore advanced data modeling, analytical techniques, and AI infrastructure improvements to strengthen platform capabilities and create new opportunities.
Stay Ahead of the Curve: Evaluate and adopt emerging data and AI tools where they add clear value, balancing innovation with stability and production reliability.
Experience needed for this role
Experience
Proven experience in Data Engineering, with a focus on platform and infrastructure.
Experience supporting AI/ML pipelines, including data preparation, model training, and deployment.
Experience implementing DevOps practices (Git, CI/CD, containerization with Docker/Kubernetes).
Passion for emerging AI/ML technologies and experience collaborating on production-ready AI/GenAI solutions.
Technical Skills
Hands-on experience with cloud platforms and data infrastructure (e.g., AWS, Snowflake, Redis).
Familiarity with modern data tools such as Databricks, dbt, Airflow, and observability/cataloguing platforms (Monte Carlo, Great Expectations, DataHub, or similar).
Strong SQL expertise for large-scale querying and optimization; experience designing and building ETL/ELT pipelines.
Proficiency in Python for data processing and AI pipeline support.
Solid understanding of data modeling and warehouse architectures, with the ability to design evolving data systems
Leadership & Communication
Ability to translate business and AI needs into scalable solutions.
Communicate effectively with technical and non-technical stakeholders.
Drive innovation to guide long-term strategy and maintain CloudPay’s competitive edge.
Languages: Excellent written and oral communication skills in English.
Education
- Degree in computer science, Engineering, Data Science, or related field; advanced degrees. Preferred NOT essential.
About you and Our core values
Taking ownership, working with integrity and respect
Being a team player is key to our culture
Solution and customer focused
Great initiative with the goal for excellence in achieving results
Dedicated to developing and always looking for continuous improvements
Be creative, be committed, be engaged and enjoy what you do
Spain Package and Benefits
Competitive Salary
Competitive vacation allowance
Calm app
Private Medical Insurance
EAP
Intensive Days
Employee Referral Program
WFH Allowance
Life Assurance
CloudPay NOW
Paid Volunteering days
Marriage Leave
Study Leave
Bereavement Leave
CloudPay is committed to being an equal opportunities employer.
#LI-AP1 #LI-HYBRID #LI-REMOTE
The CloudPay culture is built upon on five core values, from which we develop our service, our technology and our business strategies. Our fundamental beliefs are a promise to our employees, customers and partners, built on the core values of professionalism, passion, empowerment, innovation, and teamwork.Glassdoor