Digital Senior Data Engineer

About the role

The Digital Senior Data Engineer will design, develop, and maintain robust data pipelines and AI/ML solutions that power our Digital Platform, Products, and Marketing analytics. You will work across data mapping, ETL/ELT processes, and advanced AI initiatives to deliver reliable, scalable insights.

Key responsibilities

• Design and implement data maps for ingestion into the Unified Data Platform.
• Create and optimise ETL/ELT workflows in Databricks and Snowflake to ensure high performance and scalability.
• Lead AI/ML projects, from model development and deployment to monitoring using Azure tools.
• Develop NLP and deep‑learning models, applying prompt engineering and LLM frameworks.
• Conduct quality assurance, testing AI applications for accuracy, reliability, and compliance.
• Collaborate with engineers, data scientists, and business stakeholders to integrate AI solutions.
• Drive operational efficiency through AI‑driven automation and predictive analytics.
• Mentor junior engineers and promote best practices in MLOps and data engineering.

Required profile

• 4‑6 years of experience in data engineering, data science, or related fields.
• Proven ability to lead AI/ML initiatives and deliver production‑grade models.
• Strong problem‑solving skills and experience with performance optimisation.
• Excellent communication skills to convey technical concepts to non‑technical audiences.

Required skills

• Python (expert level) and SQL.
• Databricks, Snowflake, Azure ML, Azure DevOps, MLflow.
• Kubernetes, Terraform, ARM Templates, Bicep.
• Azure infrastructure (VMs, VNets, Load Balancers, Firewalls).
• Machine‑learning algorithms (classification, regression, clustering).
• LLM frameworks, Prompt Engineering, NLP techniques (tokenization, NER, speech‑to‑text).
• AI ethics, bias reduction, security and compliance.
• Low‑code/no‑code platforms, Google Analytics, Firebase, Oracle, Google Marketing Platform.