Data Engineer

Main mission

Design, build, and operate the unified data platform and domain pipelines that underpin scalable, trusted, and monetisable data products.

Key responsibilities

• Data Platform & Pipeline Engineering
• 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 Data Quality, Governance & Reliability
• 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 Enabling Analytics, ML & APIs
• Optimise datasets and pipelines for analytics, ML training, and API consumption
• Work closely with Data Scientists and ML Engineers to support feature and model needs
• Enable self‑service data access patterns for downstream teams Continuous Improvement & Scale
• Continuously improve performance, scalability, and reliability of pipelines
• Introduce modern tooling and standards to reduce operational overhead
• Contribute to long‑term platform roadmap and AI readiness Job Profile
• 5+ years experience in data engineering or platform roles
• Strong experience with SQL, Python, Spark, and cloud platforms (AWS, Azure, or GCP)
• Experience operating data platforms in production at scale Required Qualifications
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field
• MS in Big Data, AI or relevant fields
• Certifications such as PMI‑ACP, PMP, SAFe, CSM, or equivalent are beneficial