Data & AI Engineer

Starlink Qatar

Doha

On-site

QAR 240,000 - 420,000

Full time

2 days ago

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Job summary

Starlink Qatar seeks an experienced Data & AI Engineer to build enterprise-grade data products, AI-ready pipelines and APIs. You will apply software-engineering practices across data and AI delivery, including testing, CI/CD, observability and secure AI tooling.

You will design lakehouse architectures, implement data quality and governance, and enable ML/AI use cases with embeddings, vector search and RAG. Collaboration with data scientists and delivery teams is essential.

Qualifications

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.

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.

Skills

Python

SQL

Apache Spark

ETL/ELT pipelines

APIs

Git

CI/CD

Docker

Kubernetes

Airflow

Kafka

Lakehouse

Vector databases

RAG

LLMs

Data governance

Cloud platforms

Education

Bachelor's degree in Computer Science, Engineering, Information Systems

Tools

GitHub Copilot

Microsoft Copilot

Job 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.