Data Engineer

Dubai, United Arab Emirates | Posted on 01/19/2026

At Sentra

AI, Data Engineers work on live, enterprise-scale data systems that are built to run, scale, and be trusted. The pipelines you build will be used, monitored, and relied upon. When they break, you are expected to help fix them.

If you are not ready to take responsibility for production systems, this role is not for you.

The Operating Context

Sentra

AI delivers data and AI platforms inside large, complex enterprise environments with high expectations around reliability, quality, and governance.

You will be working on:

A modern cloud lakehouse architecture

Batch and real-time data pipelines

Multiple upstream systems and downstream consumers

Data that supports reporting, operations, and AI workloads

This is not greenfield. The systems are live and evolving.

Your Accountability

You are accountable for the quality and reliability of the data pipelines you build.

That includes:

Developing Spark-based batch pipelines under guidance from senior engineers

Contributing to streaming pipelines and CDC workflows

Implementing data quality checks and validations

Supporting production issues and pipeline failures

Writing clear, maintainable, testable code

Communicating clearly when something is at risk or not working

Ownership starts early and increases with capability.

Data pipelines using Apache Spark (PySpark preferred)

Bronze and Silver layer transformations in a lakehouse architecture

SQL-based transformations and aggregations

Basic streaming or near-real-time pipelines

Data quality checks using agreed frameworks

You are expected to actively use AI tools to improve development speed, testing quality, and documentation, within Sentra

AI’s defined governance standards.

You have only worked with static datasets or dashboards

You have not supported data pipelines in production

You expect requirements to always be fully defined

You avoid ownership when things fail

You are uncomfortable receiving direct technical feedback

We are explicit because the environment demands it.

What Strong Looks Like

Within 6–12 months:

Pipelines you own are stable and predictable

Data quality issues are identified and resolved early

You can debug failures with limited supervision

Senior engineers trust your contributions

You take on progressively more responsibility

This is how performance is measured.

What We Expect You To Be Strong At

SQL for transformations and analysis

Apache Spark fundamentals and distributed processing concepts

Basic understanding of data modelling and quality

Version control and collaborative development

Clear, professional communication in English

Mentorship from senior engineers and architects

Clear progression based on demonstrated capability

Real responsibility early, not shadow work

Career capital that scales beyond SentraAI

Final Note

Sentra

AI is not a training ground.

It is a place to become a serious data engineer through responsibility, delivery, and accountability.

If you want to grow by building systems that matter, we should talk.