Data Engineer – Design and Operate Unified Data Platform

About the role

The Data Engineer will design, build, and operate a unified data platform that supports scalable, trusted, and monetisable data products. You will work closely with data scientists, ML engineers, and downstream teams to enable self‑service analytics and AI readiness.

Key responsibilities

• Design and implement batch and real‑time ingestion pipelines from internal and external sources.
• Build and maintain cloud‑native data lake and warehouse architectures.
• Ensure high availability, performance, and cost efficiency of data infrastructure.
• Implement automated data quality checks, observability, and SLA monitoring.
• Support master data management, metadata, lineage, and access controls.
• Embed security, privacy, and compliance controls into the platform by design.
• Optimise datasets and pipelines for analytics, ML training, and API consumption.
• Collaborate with Data Scientists and ML Engineers to support feature and model needs.
• Enable self‑service data access patterns for downstream teams.
• Continuously improve performance, scalability, and reliability of pipelines.
• Introduce modern tooling and standards to reduce operational overhead.

Required profile

• 5+ years of experience in data engineering or platform roles.
• Strong experience with SQL, Python, Spark, and cloud platforms (AWS, Azure, or GCP).
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field; MS in Big Data, AI, or relevant fields is a plus.
• Relevant certifications such as PMI‑ACP, PMP, SAFe, CSM are beneficial.

Required skills

• SQL
• Python
• Apache Spark
• Cloud platforms (AWS, Azure, GCP)