Data Engineer

CNTXT AI

Abu Dhabi

On-site

AED 300,000 - 420,000

Full time

2 days ago

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Job summary

CNTXT AI is seeking a Data Engineer to design and scale data infrastructure powering analytics and AI products. You will build robust data pipelines, integrate sources, ensure data quality, and enable accessible data across teams.

You'll work with engineers, data scientists, and product managers to deliver reliable, high-performance data solutions in a modern cloud stack with CI/CD practices and comprehensive governance.

Qualifications

Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field.

Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
Build and manage modern data warehouses and data lakes.
Develop reliable batch and real-time data processing pipelines.
Integrate data from APIs, databases, third-party platforms, and cloud services.
Ensure data quality, integrity, security, and governance.
Optimize data models and database performance for analytics and reporting.
Monitor, troubleshoot, and improve data pipeline reliability and performance.
Collaborate with Data Scientists, ML Engineers, Product Managers, and Software Engineers to deliver data solutions.
Implement CI/CD practices and infrastructure automation for data workflows.
Document data architecture, pipeline designs, and engineering best practices.
Stay current with emerging technologies in cloud data engineering and big data ecosystems.

Skills

Python

SQL

ETL/ELT pipelines

Cloud platforms

CI/CD practices

Collaboration

Education

Bachelor's degree in Computer Science

Tools

Airflow

Dagster

Prefect

Kubernetes

Docker

Spark

Snowflake

BigQuery

Redshift

Azure Synapse

PostgreSQL

MySQL

MongoDB

dbt

Terraform

Job description

Location: Onsite - AbuDhabi UAE
Employment Type: Full-Time
Department: Engineering / Data & AI

Data Engineer

About the Role

We are looking for a skilled Data Engineer to build, optimize, and maintain scalable data infrastructure that powers analytics, AI, and machine learning products. You will be responsible for designing robust data pipelines, integrating data from multiple sources, ensuring data quality, and enabling data accessibility across the organization.

This role is ideal for someone who enjoys solving complex data challenges, building modern data platforms, and working closely with software engineers, data scientists, and product teams to transform raw data into business value.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
Build and manage modern data warehouses and data lakes.
Develop reliable batch and real-time data processing pipelines.
Integrate data from APIs, databases, third-party platforms, and cloud services.
Ensure high standards of data quality, integrity, security, and governance.
Optimize data models and database performance for analytics and reporting.
Monitor, troubleshoot, and improve data pipeline reliability and performance.
Collaborate with Data Scientists, ML Engineers, Product Managers, and Software Engineers to deliver data solutions.
Implement CI/CD practices and infrastructure automation for data workflows.
Document data architecture, pipeline designs, and engineering best practices.
Stay current with emerging technologies in cloud data engineering and big data ecosystems.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field.
4+ years of experience in Data Engineering or Backend/Data Platform development.
Strong proficiency in Python and SQL.
Experience building ETL/ELT pipelines using modern orchestration tools such as Airflow, Prefect, or Dagster.
Strong knowledge of relational and NoSQL databases including PostgreSQL, MySQL, MongoDB, or Cassandra.
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Hands-on experience with cloud data warehouses such as Snowflake, BigQuery, Amazon Redshift, or Azure Synapse.
Experience with distributed data processing frameworks such as Apache Spark.
Familiarity with message streaming technologies such as Kafka or RabbitMQ.
Experience with Docker, Kubernetes, and CI/CD pipelines.
Strong understanding of data modeling, partitioning, indexing, and performance optimization.
Experience working with Git and collaborative software development workflows.

Preferred Qualifications

Experience building data platforms supporting AI or Machine Learning workloads.
Knowledge of Delta Lake, Apache Iceberg, or Apache Hudi.
Experience with dbt for analytics engineering.
Familiarity with Terraform or Infrastructure as Code.
Understanding of data governance, metadata management, and data cataloging.
Experience working in high-growth technology or AI companies.

Technical Stack

Languages: Python, SQL
Databases: PostgreSQL, MySQL, MongoDB
Data Processing: Apache Spark, Pandas
Orchestration: Apache Airflow, Prefect, Dagster
Streaming: Kafka, RabbitMQ
Cloud: AWS, Azure, GCP
Data Warehouse: Snowflake, BigQuery, Redshift, Synapse
Containerization: Docker, Kubernetes
Version Control: Git
Infrastructure: Terraform (preferred)

What We're Looking For

Strong analytical and problem-solving skills.
Excellent understanding of scalable data architecture.
Ability to work independently in a fast-paced environment.
Strong communication and collaboration skills.
Passion for building reliable, high-performance data systems.
Continuous learning mindset and enthusiasm for modern data technologies.

Nice to Have

Experience supporting Generative AI or LLM applications.
Experience with vector databases such as Pinecone, Weaviate, or Milvus.
Familiarity with data observability platforms such as Monte Carlo or Great Expectations.
Experience with event-driven architectures and real-time analytics.
Exposure to MLOps platforms and feature stores.

Why Join Us?