Data Engineer

About the role

The Data Engineer will design, develop, and optimise data platforms that enable the organisation’s analytics and business intelligence initiatives. Working with Databricks and modern lake‑house technologies, you will ensure the platform is scalable, high‑performing, secure and cost‑effective.

Key responsibilities

• Implement scalable, high‑performance data platform architecture using Databricks.
• Lead the creation and standardisation of data engineering pipelines and related tools.
• Collaborate with data scientists, analysts and business stakeholders to align platform solutions with strategic objectives.
• Design, develop and maintain data ingestion, storage, transformation and query layers, supporting both batch and real‑time processing.
• Optimise data lake, lake‑house and ODS structures for performance, cost and reliability.
• Develop and manage data warehousing solutions, including data modelling, schema design and performance tuning.
• Implement robust ETL/ELT processes, data quality controls and governance compliance.
• Provide technical expertise and guidance for all data platform initiatives.

Required profile

• At least 84 months (7 years) of hands‑on experience in data engineering and platform development.
• Deep understanding of data architecture, lake‑house concepts and big‑data technologies.
• Proven ability to design scalable, secure and cost‑efficient data solutions.
• Strong collaboration skills to work with cross‑functional teams.

Required skills

• Data engineering pipelines
• Data platform engineering
• Lake house
• Data storage structures
• Data quality controls
• Data orchestration
• ELT
• ODS
• ETL
• Big Data Technologies
• Data Lake
• Data Architecture
• Data Warehousing
• Data Integration
• Databricks
• Data Modelling