Data Engineer

G42 is hiring a Data Engineer in Abu Dhabi, United Arab Emirates. Level rates it ; you can apply on G42.

Level's read on this job

On Level's scale, this data engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include OpenAI, LangChain and Databricks.
Level classifies it as a mid-level role.
Level lists 57 other open roles at G42.

AI in this role

Build scalable data pipelines and intelligent AI solutions including RAG pipelines and LLM integrations on cloud infrastructure.

OpenAILangChainDatabricksN8nAzurePythonSQLPySparkDockerKubernetes

ragai-agentsml-opsdata-engineeringvector-databasesetlmlopsapi-development

Inception42, a G42 company, is the region’s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer – transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact. For more information, please visit www.inception42.ai

Overview:

We are looking for a Data Engineer who can build scalable data pipelines while also developing intelligent AI solutions using Azure Agent Foundry, OpenAI services, LangChain, Databricks, and modern cloud architectures. The ideal candidate has strong data engineering foundations combined with hands-on experience designing and deploying enterprise-grade AI systems.

Responsibilities:

What You’ll Own

Develop and deploy AI agents using Azure Agent Foundry, OpenAI, LangChain, and N8N.
Build RAG pipelines, embeddings, vector database integrations, and knowledge graph solutions.
Design and maintain scalable data pipelines, ETL/ELT workflows, and data architectures.
Build and maintain APIs and data services supporting AI and analytics workloads.Optimize ML workflows on Azure Databricks and integrate with Azure Fabric.
Ensure data quality, reliability, governance, and compliance across all systems.
Collaborate with data scientists, ML engineers, and product teams to deliver intelligent features.
Support MLOps and DevOps processes including CI/CD, model lifecycle management, and containerized deployments.

Qualifications:

What We’re Looking For

Bachelor’s in Computer Science, Engineering, Data Science, or related field.
3+ years experience in Data Engineering, AI Engineering, or ML Engineering roles.
Experience delivering scalable AI/data solutions in cloud environments (Azure preferred).
Strong proficiency in Python, SQL, PySpark, and ML/AI frameworks.
Experience with Azure Agent Foundry, OpenAI APIs, LLMOps, RAG systems, and vector databases.
Hands-on experience with Azure Databricks, Azure cloud services, and data platforms.Knowledge of big data tools (Spark, Hadoop, Flink) and modern data storage (SQL, NoSQL).
Experience with REST/GraphQL APIs, Kafka/RabbitMQ, Docker/Kubernetes.
Solid understanding of data modeling, ETL, and data quality best practices.Strong problem-solving, communication, and cross-functional collaboration skills.

What We Look ForIf you are a performance-driven, inquisitive mind with the agility to adapt to ambiguity, you will fit right in. You should be eager to explore opportunities to build meaningful collaborations with stakeholders and aspire to create unique customer-centric solutions. Bias for action and a passion to conquer new frontiers in the AI space is at the heart of the Inception42 community. What Working At Inception42 Offers Culture: An open, diverse and inclusive environment with a global vision that encourages personal growth and focuses on ground-breaking, industry-first innovations.Career: Outstanding learning, development & growth opportunities via structured training programs and innovative, high-tech projects.Rewards: A competitive remuneration package with a host of perks including healthcare, education support, leave benefits and more. If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.

How we rate this

Data Engineer at G42 rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Engineer is an open job at G42.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Abu Dhabi, Abu Dhabi, United Arab Emirates.
The job was posted on September 4, 2026.
Seniority: mid.
Applications are handled by G42. Apply on G42

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsML OpsData EngineeringVector databasesETLMLOpsAPI Development

Also common in data engineer jobs at this level

AWS Machine learning Airflow Generative AI Snowflake Google Cloud

Pay

Typical data engineer job: $145k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
How do you monitor a model once it's live, and how do you know it needs retraining?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where vector databases was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: RAG, AI agents, ML Ops, Data Engineering, and Vector databases. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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