Data Engineer

About the role

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