Data Engineer

Salt; Dubai; On-site; AED 201,000 - 268,000; Full time

Job summary

Salt in Dubai is seeking an experienced Data Engineer who excels at data modeling and hands-on data engineering to support banking analytics. You will design data marts and semantic models beyond traditional ETL, focusing on customer 360, accounts, products, and transactions.

You will leverage SQL and Python skills with AWS Redshift, Airflow, and Spark to deliver production-ready datasets for AI/ML use cases and business insights.

Qualifications

• Hands-on data modeling and data architecture experience.
• Deep understanding of banking data (Customer 360, accounts, products, transactions).
• Ability to translate business requirements into data models and production datasets.

Responsibilities

• Design and develop data marts and semantic data models.
• Build daily and monthly customer-level datasets for insights and AI/ML use cases.
• Deliver production-ready datasets with validated quality and performance.

Skills

Data Modeling

SQL

Python

Analytical thinking

Banking domain understanding

Tools

AWS Redshift

Airflow

Spark

CI/CD

Job description

Salary - AED 18,000 - AED 24,000 Per Month

Contract Length - 1 Year (View to extend)

Location - Dubai with occasional travel to Abu Dhabi

Start Date – ASAP

The client is looking for experienced, hands‑on Data Engineers with strong Data Modeling expertise and a solid understanding of Banking Analytics. They are not looking for traditional Data Engineers whose experience is mainly focused on ETL, data ingestion, or cloud infrastructure.

The key expectations are:

• Strong experience in designing and developing data marts, semantic data models, and analytical datasets, rather than just building ETL pipelines.
• Good understanding of Retail, Corporate, and SME banking data, particularly Customer 360, customer accounts, products, transactions, AUM, and customer behavior.
• Experience developing daily and monthly customer‑level datasets and analytical features to support business insights and AI/ML use cases.
• Ability to independently translate banking business requirements into data models, write the necessary code, and deliver production‑ready datasets.
• Strong hands‑on SQL and Python skills, with AWS Redshift experience being particularly important.
• Experience with data pipelines, workflow orchestration, CI/CD, and bronze, silver, and gold data architecture.
• Experience with Airflow and Spark would be valuable, particularly for developing transformations and integrating datasets into the gold layer.
• Understanding of how Data Science teams consume analytical datasets. Hands‑on ML model development is a plus but not mandatory.

The main priority is to identify candidates who combine strong Data Modeling capabilities, hands‑on Data Engineering skills, and a solid understanding of banking business processes and data.

I am not looking for traditional Data Engineers. Candidates with hands‑on Data Architecture, Data Modeling, or Banking Analytics backgrounds could also be suitable, providing you have strong development skills.