BI Engineer (Hybrid or Onsite) at Viva.com

Municipality of Marousi, Attica, Greece -

Full Time

Start Date

Immediate

Expiry Date

08 Mar, 26

Salary

0.0

Posted On

08 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

BI Engineering, Data Foundations, Advanced Analytics, AI, Machine Learning, Data Modeling, SQL, KQL, DAX, Power BI, Data Visualization, Cloud Platforms, Python, Git, CI/CD, Analytical Skills

Industry

Financial Services

Description

Viva.com, the 1st Tech Bank in Europe for Businesses, revolutionises omnichannel payments acceptance, offers card issuing, loans and deposit accounts. Viva.com is the first to pioneer and holds the top position in the Tap on Any Device technology, enabling payments acceptance on any device or even without a device. Today Viva.com is leading the transition to All-in-One business solutions, powered by its full suite of financial services. To that end, reflecting its holistic approach to business needs, Viva.com has built a dynamic ecosystem featuring over 450 tech partner-innovators in the software and hardware space. Connecting directly to all local payment schemes, alternative payment methods and payment systems across the continent, further strengthens Viva.com’s value proposition. Viva.com envisions to provide businesses a value-driven platform to accelerate the adoption of the latest technology. The Role As a BI Engineer you will play a key role in designing and optimizing the data foundations that power our advanced analytics, AI, and agentic capabilities. Working at the intersection of business intelligence, machine learning, and large language models, you will build semantic models, prepare AI-ready datasets, and enable LLM-driven insights across the organization. By leveraging modern data platforms, automation, and scalable architectures, you will ensure high-quality, reliable data that fuels smarter decision-making and accelerates Viva.com’s AI-first strategy. Responsibilities Design semantic models supporting Power BI, LLM inputs, and ML/agentic pipelines. Demonstrate proficiency in SQL, KQL, DAX and complex data analysis. Own and evolve Silver and Gold data layers within the BI architecture. Optimize existing Power BI semantic models for performance and usability. Prepare AI/LLM-ready datasets for advanced analytics and generative AI use cases. Perform tasks efficiently and within agreed timelines. Continuously expand technical knowledge and expertise. Identify, design, and implement improvements—including automation and optimized data delivery. At Viva.com, we believe in amplifying human potential through AI. When you join us, you're stepping into a future-forward environment where technology empowers every role, driving smarter, more efficient. Minimum 2 years of relevant working experience as BI Engineer or similar data/BI role Bachelor’s degree in Computer Science, Data Science, Mathematics, or related field. Strong understanding of data modeling, versioning, and BI best practices. Experience with relational (SQL Server, MySQL) and NoSQL databases (MongoDB, CouchDB). Proficiency in SQL, KQL, DAX, and semantic model design/optimization. Advanced data visualization skills (Power BI, Tableau). Familiarity with cloud platforms (Azure, GCP, AWS) and modern data architectures. Experience preparing AI/LLM-ready datasets and supporting ML/agentic pipelines. Programming skills in Python and hands-on experience with Git and CI/CD pipelines. Strong analytical, communication, and collaboration skills; fluency in English. 💸 Competitive compensation package; 🎯Annual bonus based on your performance and targets’ achievement; 🏥 Private health insurance for you and your family; 💻 Top of the Line tools and equipment; 📚 Career development and regular feedback to develop your skills; 🏃🏽‍♂️ Employee Wellness Program like Daily group sessions led by professional coaches.

Responsibilities

As a BI Engineer, you will design and optimize data foundations for advanced analytics and AI capabilities. You will build semantic models and prepare AI-ready datasets to enable insights across the organization.