Data Engineer

DISCOVERED; Abu Dhabi; On-site; AED 240,000 - 420,000; Full time

Job summary

DISCOVERED partners with a leading financial services organisation in Abu Dhabi to advance its Data & AI capabilities. We seek an experienced Data Engineer to build scalable data infrastructure and pipelines powering AI/ML across the business.

This is a hands-on role; you’ll collaborate with AI/ML and software teams to ensure reliable, high-quality data at scale, while enforcing data quality, governance and security across the data lifecycle.

Qualifications

• 5+ years of experience in Data Engineering, ETL development, data warehousing or similar roles.
• Hands-on ETL/ELT workflow design with Airflow, dbt, Luigi or equivalent.
• Strong Python and SQL skills; knowledge of Scala or Java a plus.
• Experience with big data architectures and large-scale pipelines.
• Cloud data environments across Azure, AWS or GCP.
• Experience handling large-scale structured and unstructured data.
• Data quality, governance, monitoring and engineering best practices.
• Problem-solving to diagnose performance and data issues.
• Bachelor’s degree in Computer Science, Engineering or related field.

Responsibilities

• Design, build and optimise scalable ETL/ELT pipelines.
• Develop data infrastructure for AI/ML workloads.
• Test, monitor and optimise pipelines for reliability and data integrity.
• Collaborate with AI/ML and software teams to provide accessible data.
• Maintain data architecture, lineage and metadata documentation.

Skills

ETL development

Python

SQL

Data pipeline design

Data governance

Education

Bachelors in CS/Engineering

Tools

Airflow

dbt

Luigi

Scala

Java

Job description

Discover the Opportunity

We’re partnering with a leading financial services organisation in Abu Dhabi that is continuing to invest heavily in its Data & AI capabilities.

They’re looking for an experienced Data Engineer to build the scalable data infrastructure and pipelines that underpin advanced AI and machine learning solutions across the business.

This is a hands-on engineering role where you’ll work closely with AI, ML and software engineering teams, ensuring they have access to reliable, high-quality data at scale.

Discover the Responsibilities

• Design, build and optimise scalable ETL/ELT pipelines to ingest, process and transform structured and unstructured data.

• Develop reliable data infrastructure capable of supporting large-scale AI, machine learning and analytics workloads.

• Continuously test, monitor and optimise data pipelines to improve performance, reliability and data integrity.

• Work closely with AI/ML and software engineering teams to make high-quality data easily accessible for downstream applications.

• Implement strong data quality, validation, governance and security practices across the data lifecycle.

• Maintain clear documentation around data architecture, lineage and metadata.

Discover the Requirements

• 5+ years of experience in Data Engineering, ETL development, data warehousing ors imilar positions.

• Strong hands-on experience designing and managing ETL/ELT workflows using technologies such as Airflow, dbt, Luigi or similar.

• Excellent Python and SQL skills, alongside experience with Scala, Java or another relevant programming language.

• Experience working with big data architectures and optimising large-scale data pipelines.

• Hands-on experience with cloud data environments across Azure, AWS or GCP.

• Experience processing and managing large-scale structured and unstructured datasets.

• Strong understanding of data quality, governance, monitoring and engineering best practices.

• Excellent problem-solving skills with the ability to diagnose performance and data issues.

• Bachelor’s degree in Computer Science, Engineering or a related technical discipline.

Why Join?

• Work on large-scale Data & AI initiatives within a highly ambitious technology environment

• Build the data foundations behind production AI and machine learning solutions

• Work alongside experienced Data, AI, ML and Software Engineers

• Take ownership of technically challenging data engineering problems with genuine business impact