Data Engineer – Build Scalable Data Platforms

About the role

You will play a key role in designing and operating a modern, unified data platform that transforms raw data into trusted, high‑value data products. Join a global team focused on AI‑enabled analytics and data‑driven decision making.

Key responsibilities

• Build robust batch and real‑time data pipelines from diverse sources.
• Develop and maintain cloud‑native data lake and warehouse solutions.
• Ensure high availability, performance, and cost efficiency of data platforms.
• Implement data quality checks, observability, and SLA monitoring.
• Support data governance, metadata, lineage, and access‑control frameworks.
• Embed security, privacy, and compliance by design.
• Optimize datasets for analytics, machine learning, and API consumption.
• Collaborate with data scientists and ML engineers to enable self‑service data capabilities.
• Continuously improve scalability, performance, and reliability using modern tools and best practices.

Required profile

• 5+ years of experience in data engineering or data platforms.
• Strong background in Python, SQL, Spark and cloud environments (AWS, Azure or GCP).
• Hands‑on experience managing production‑scale data platforms.
• Solid understanding of data architecture, pipelines, and governance.
• Bachelor’s degree in Computer Science, Engineering or related field (Master’s in Big Data/AI is a plus).
• Relevant certifications (e.g., PMP, SAFe, CSM, PMI‑ACP) are a bonus.

Required skills

• Python
• SQL
• Apache Spark
• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

What we offer

• Work on high‑impact, global data initiatives.
• Shape the future of AI‑driven data products.
• Collaborate with top‑tier data and product experts.
• Be part of a mission‑driven organisation making a real difference.