Data Engineer
5 hours ago
About Runestone Intelligence
Runestone Intelligence is a global AI and data innovation company headquartered at the DIFC AI Campus, Dubai — with strong Nordic roots and growing presence across Europe, the Middle East, and South Asia.
We work on world-class AI projects spanning retail, fintech, maritime, and sustainability sectors — developing end-to-end data and machine learning solutions that power real-world decisions.
Role Overview
We are looking for a
Data Engineer / ML Engineer
with strong
Databricks
experience to join our growing global engineering team.
You'll help design, build, and optimize scalable data and ML pipelines in a cloud environment (Azure / GCP / AWS), enabling real-time analytics, AI model deployment, and business intelligence at scale.
Key Responsibilities
- Design and implement data pipelines for ingestion, transformation, and storage using
Databricks - Work with
Spark, Delta Lake
, and
MLflow
to manage and monitor ML workloads - Collaborate with data scientists and product teams to deploy ML models into production
- Optimize performance and cost-efficiency across cloud infrastructure
- Maintain CI/CD and data quality processes for production pipelines
- Contribute to architecture discussions and innovation in AI-driven products
Requirements
Proven experience in
Data Engineering or ML Engineering
(3+ years preferred)
Hands-on experience with
Databricks
(Workspace, Unity Catalog, Delta Live Tables, MLflow)
Strong knowledge of
Python
,
SQL
, and
PySpark
Experience with
Azure, GCP, or AWS
data ecosystems
Solid understanding of modern data architectures (lakehouse, ETL/ELT, orchestration)
Databricks certification
(e.g.
Data Engineer Associate / Professional
,
Machine Learning Associate
) is a big plus
Experience with
Docker, Airflow, Terraform, or CI/CD
pipelines is a plus
What We Offer
A chance to work on high-impact AI projects across industries and continents
Global collaboration with experts in AI, analytics, and engineering
Flexible location & working setup
Long-term growth opportunities within a fast-scaling AI firm
How to Apply
apply directly here on LinkedIn.
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