DataOps Engineer at Eeze focusing on data pipeline stability across multiple products. Collaborating with IT teams to maintain quality, observability, and operational efficiency.
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
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Data Engineer developing and enhancing data pipelines and models at ERNI Schweiz. Required skills include SQL and Python with opportunities for remote work in Europe.
Senior Data Engineer developing ETL and data pipelines for Burlington’s digital transformation team. Collaborating with analytics and engineering teams to support insights from data analysis.
Data Engineer responsible for Azure SQL database development in a leading Norwegian damage service company. Engage in data quality, integration, and collaboration on analytical tools.
GCP Data Engineer responsible for building and optimizing scalable data pipelines using GCP services. Develop, maintain, and ensure data quality in ETL/ELT workflows with Python and SQL.
Experienced Database Administrator managing SQL Server environments and cloud data engineering. Collaborating with teams to optimize data solutions at Clear Channel Outdoor.
Data Engineer designing modern data infrastructures and pipelines for restaurant industry improvement. Collaborating with teams to ensure data quality and accessibility for strategic decisions.
Data Engineer specializing in Databricks at Sogeti implementing large - scale data processing solutions. Collaborating with Data Scientists and optimizing ETL processes for data engineering best practices.
Data Engineer at the forefront of digital transformation, implementing modern database structures and pipelines. Collaborating closely with clients to ensure data quality and system stability.
Senior Data Engineer designing and implementing scalable data architectures and pipelines for clients. Collaborating in agile teams while utilizing modern data platforms and cloud environments.