We are looking for a Senior Data Engineer to design, build and maintain scalable data systems that support analytics and machine learning initiatives. This role operates in a hybrid environment (SaaS and on-premise) and plays a key part in structuring and optimising the data flow across the platform.

Responsibilities:

Design, develop and maintain scalable ETL/ELT data pipelines using Python

Process and integrate data from multiple formats and sources, including JSON, CSV and XML

Build and manage data transformations and orchestration flows using DBT and tools such as Airflow, Prefect or Dagster

Ensure data governance, quality and security standards are upheld across data systems

Extend, maintain and optimise the Elastic Hierarchy data framework

Work closely with analytics, machine learning and product teams to deliver reliable, business-ready datasets

Support data operations in hybrid environments (SaaS and on-premise)

Requirements / Skills:

Undergraduate or postgraduate degree in Computer Science, Data Engineering or a related field

Solid experience in Python development

Experience with the AWS data ecosystem, including services such as S3, Glue, Lambda, EMR, EC2, Redshift and RDS

Practical experience with Snowflake, MongoDB and PostgreSQL

Experience with DBT and at least one orchestration tool (Airflow, Prefect or Dagster)

Knowledge of data mapping, attribution and reconciliation processes

Ability to work in hybrid and on-premise environments

High level of English, both written and spoken