Data Engineer

Role & Responsibilities

• Design curated analytical models aligned with Medallion architecture
• Build certified, reusable datasets optimised for PowerBI
• Guarantee data quality, lineage and business meaning
• Engineer scalable transformations using Databricks / Spark
• Implement pipelines in SQL, Python, Scala or Java
• Optimize performance, cost and reliability across batch and streaming workloads
• Embed testing, monitoring and CI-CD into data pipelines
• Build and operate data platforms on Azure
• Contribute to cloud-native architecture, automation and governance
• Develop scalable transformations in Databricks / Spark
• Develop Front-ends using datasources and APIs

Preferred Candidate Profile

We are looking for engineers with solid foundations (at least 3-4 years of experience) and a willingness to operate across the stack.

Core Skills

• Azure Cloud engineering (Data Lake, ADF, Key Vault, Functions, etc.)
• Databricks + Spark (structured streaming, performance tuning)
• SQL (advanced modelling and optimisation)
• Python, C#
• JavaScript/TypeScript
• Medallion Architecture
• Apache Kafka (topics, partitions, consumer groups, event-driven architectures, stream processing)
• Experience building and operating real-time data pipelines using Kafka and Spark Streaming
• Kubernetes knowledge (deployment, orchestration, scaling)
• Experience in lakehouse architectures
• Interest in UX/data storytelling