Data Engineer

This is not a junior role.

At SentraAI 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

SentraAI 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.

What You Will Build

• 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 SentraAIs defined governance standards.

Requirements

This Role Is Not For You If

• 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 612 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

• Python for data engineering

• 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

Benefits

What SentraAI Gives in Return

• Hands-on exposure to enterprise-scale data systems

• 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

SentraAI 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.