Join a certified Databricks partner working at the forefront of AI, Big Data, and Advanced Analytics. Our client is a Hungary-based tech company delivering end-to-end, cloud-native data solutions for both local and global enterprise clients.
You’ll work on two types of engagements: As a consulting architect, helping strategic clients implement scalable, production-grade data platforms using Databricks and Apache Spark. As part of an augmented team within Databricks, providing hands-on architecture expertise across high-impact projects.
This is a senior, customer-facing role where your Spark skills, cloud experience, and ability to communicate with stakeholders will make a real business impact. You’ll be part of a team that values continuous learning, technical excellence, and knowledge-sharing across the data community.
What You’ll Do — Lead the design and implementation of big data architectures using Spark and Databricks. — Guide customers from PoC to production, aligning data platforms with business goals. — Optimize pipelines and performance at scale across cloud platforms (AWS, Azure, GCP). — Share your knowledge via internal training, customer enablement, and community events.
What We’re Looking For — 5+ years as a Data/Software Engineer with deep Spark expertise. — Hands-on experience delivering multiple projects on Databricks. — Databricks Certified Data Engineer Professional (must-have). — Proficiency in Python, Scala, or Java. — Experience with cloud-native data platforms (AWS/Azure/GCP). — Familiarity with CI/CD, orchestration tools, APIs, SQL interfaces, and testing practices. — Strong communication and consulting skills — you enjoy engaging with clients. — Bonus: Experience with ML lifecycle tools (e.g., MLflow), model deployment, deep learning.
Why Join? ✔ Work with global clients and Databricks directly ✔ Flexible remote work with European timezone alignment ✔ Collaborative, senior-level team with continuous learning culture ✔ Build future-proof, vendor-neutral solutions for data-driven enterprises
