Data Engineer – Cloud Native & AI

About the role

We are seeking an experienced Data Engineer to join a high‑performing data and analytics team driving enterprise‑wide transformation initiatives. The role focuses on building modern, cloud‑native data platforms that support analytics, business intelligence and machine learning across the organisation.

Key responsibilities

• Design, develop and optimise scalable batch and real‑time data pipelines.
• Build and maintain enterprise data lakes, lakehouse architectures and curated analytical datasets.
• Write high‑performance SQL and Python code for large‑scale data processing workloads.
• Implement data quality, validation, monitoring and observability frameworks.
• Deploy cloud‑native data solutions using infrastructure‑as‑code practices.
• Collaborate with Data Scientists, BI teams and business stakeholders to deliver trusted, governed data products.
• Support AI and machine‑learning initiatives by preparing training datasets and enabling MLOps workflows.

Required profile

• 5+ years of professional experience in data engineering.
• Proven ability to design and build ETL/ELT pipelines at scale.
• Strong expertise in SQL and Python.
• Hands‑on experience with Azure cloud data services.
• Familiarity with modern data warehousing and lakehouse concepts.
• Experience with CI/CD and infrastructure automation.

Required skills

• Microsoft Fabric
• Azure Data Factory (ADF)
• Databricks
• PySpark
• Python
• Advanced SQL
• Lakehouse Architecture & Delta Lake
• Azure Synapse Analytics
• Terraform & Infrastructure as Code (IaC)
• GitHub Actions & Azure DevOps
• Data Governance & Data Quality Frameworks
• Change Data Capture (CDC)
• API Integrations
• Streaming Data Pipelines
• MLOps Enablement
• Metadata Management & Data Lineage
• Scala (nice to have)
• Hadoop ecosystem (nice to have)