# Data & AI Engineer — Starlink Qatar

Canonical: https://jobxdubai.com/jobs/li-4469745403-data-ai-engineer
Location: Doha, Qatar
Type: full_time · Level: senior
Monthly salary: AED 18,162 to 32,288 per month (estimated, not employer-stated) (UAE salaries are tax-free)
Posted: 2026-09-24
Apply: https://www.linkedin.com/jobs/view/data-ai-engineer-at-starlink-qatar-4469745403?_l=en

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## Description

We are looking for an experienced Data & AI Engineer to join our team and contribute to enterprise and public-sector digital, data, cloud and AI platform engagements.

The role focuses on building production-grade data products, AI-ready data pipelines and software services that ingest, transform, govern and serve both structured and unstructured data.

You will apply strong software-engineering practices across data and AI delivery, including modular development, APIs, automated testing, CI/CD, observability, security and responsible use of AI-assisted coding tools.

Key Responsibilities

• Develop and maintain batch and real-time/streaming data ingestion and transformation pipelines.

• Design and implement lakehouse architectures, curated data models, data products and serving APIs.

• Implement data quality, metadata, lineage, classification and access-control mechanisms.

• Build data pipelines supporting ML/AI use cases, document processing, embeddings, vector search and RAG solutions.

• Develop modular, maintainable and production-ready solutions using Python, SQL and Apache Spark.

• Implement automated testing, code reviews, CI/CD and deployment practices.

• Work with cloud platforms, containers, orchestration and monitoring/observability tools.

• Troubleshoot data and application issues and provide operational support for production workloads.

• Use approved AI coding assistants such as GitHub Copilot, Microsoft Copilot or equivalent enterprise-approved tools to support development, testing, documentation and analysis.

• Independently validate AI-generated code and ensure correctness, security, licensing compliance, performance and maintainability.

• Collaborate with data scientists, software engineers, architects, business stakeholders and delivery teams.

Required Skills & Experience

• 5+ years of professional experience in data engineering, AI engineering, software engineering or a closely related field.

• Strong hands-on experience with Python and SQL.

• Experience developing ETL/ELT pipelines and data processing solutions.

• Strong knowledge of Apache Spark and modern data/lakehouse architectures.

• Experience with batch and streaming data processing.

• Experience with APIs, Git, automated testing and CI/CD.

• Exposure to cloud data platforms, containers, orchestration and observability.

• Understanding of ML data preparation, embeddings, vector databases/search and Retrieval-Augmented Generation (RAG).

• Understanding of data governance concepts including data quality, lineage, metadata and access control.

• Experience working in complex enterprise or public-sector environments is highly desirable.

• Demonstrated ability to independently review and validate AI-generated code.

Education & Certifications

• Bachelor's degree in Computer Science, Engineering, Information Systems or a related discipline.

Preferred Certifications

• Databricks Certified Data Engineer Associate

• Microsoft Certified: Azure Data Engineer Associate

• AWS Certified Data Engineer – Associate

• Google Cloud Professional Data Engineer

• Microsoft Certified: Azure AI Engineer Associate

Preferred Technologies

Experience with some of the following will be advantageous:

Python | SQL | Apache Spark | Databricks | Azure/AWS/GCP | APIs | Git/GitHub | CI/CD | Docker | Kubernetes | Kafka | Airflow | Lakehouse | Vector Databases | RAG | LLMs | Data Governance | GitHub Copilot | Microsoft Copilot

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## Requirements

- 5+ years of professional experience in data engineering, AI engineering, software engineering or a closely related field.
- Strong hands-on experience with Python and SQL.
- Experience developing ETL/ELT pipelines and data processing solutions.
- Strong knowledge of Apache Spark and modern data/lakehouse architectures.
- Experience with batch and streaming data processing.
- Experience with APIs, Git, automated testing and CI/CD.
- Exposure to cloud data platforms, containers, orchestration and observability.
- Understanding of ML data preparation, embeddings, vector databases/search and Retrieval-Augmented Generation (RAG).
- Understanding of data governance concepts including data quality, lineage, metadata and access control.
- Experience working in complex enterprise or public-sector environments is highly desirable.
- Demonstrated ability to independently review and validate AI-generated code.

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