Data Engineer focused on analytics and data pipeline development for network optimisation. Collaborating with teams to deliver high - quality data solutions with Python and SQL.
About the role
- Data Engineer responsible for building CloudPay's modern data platform for payroll and HR solutions. Collaborating across teams to optimize data pipelines and AI initiatives in a fast-paced environment.
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.
Requirements
- 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.
- 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.
- 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.
- Excellent written and oral communication skills in English.
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
Job title
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Experience level
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Not specified
Degree requirement
Tech skills
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