Data Engineer for Production AI Pipelines

talentbridgedubai; Dubai; On-site; AED 180,000 - 280,000; Full time

Job summary

talentbridgedubai is seeking an experienced data engineer to build robust, observable data pipelines powering research and production AI. You will partner with AI/ML, analytics, and product teams to ensure reliable on-time delivery and trustworthy data.

Responsibilities include architecting batch/stream ETL, enforcing data quality and governance, supporting ML workflows with DVC/MLflow, building feature stores and secure REST endpoints, and maintaining internal catalogs for self-service

Qualifications

• Skills: C++/Java, SQL/NoSQL, Pandas/NumPy, PySpark, Airflow, API development, Docker.
• MLOps: DVC, MLflow or W&B, model packaging/deployment fundamentals.
• Cloud: AWS SageMaker, Azure ML, or GCP AI experience.
• Nice to have: Unreal Engine exposure.
• Environment: Linux background for development and deployment.
• Education/Experience: Proven experience building reliable pipelines in production.

Responsibilities

• Architect and operate batch/stream pipelines (Airflow; Spark optional) for ETL/ELT.
• Model/manage schemas; enforce data quality and lineage/governance.
• Support ML workflows with DVC and MLflow or Weights & Biases.
• Build feature stores/data services; expose datasets via secure REST endpoints.
• Maintain documentation and internal catalogs; enable self-service analytics.

Skills

C++/Java programming

SQL/NoSQL

Pandas/NumPy

PySpark

Airflow

API development

ML/DL tooling

DVC

MLflow / Weights & Biases

Cloud: AWS SageMaker/Azure ML/GCP

Linux

Unreal Engine (nice to have)

Tools

Docker

Job description

talentbridgedubai is seeking an experienced data engineer to build robust, observable data pipelines powering research and production AI. You will partner with AI/ML, analytics, and product teams to ensure reliable on-time delivery and trustworthy data.

Responsibilities include architecting batch/stream ETL, enforcing data quality and governance, supporting ML workflows with DVC/MLflow, building feature stores and secure REST endpoints, and maintaining internal catalogs for self-service