Data Engineer

Artefact

Doha

Presencial

QAR 120.000 - 240.000

Jornada completa

14 días+

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Descripción de la vacante

Artefact is hiring a Data Engineer in Doha to design and maintain robust data pipelines using Python and SQL. You will manage databases, integrate cloud services (Azure, GCP, AWS), and collaborate with teams to deploy ML-enabled data solutions, leveraging Spark and Kafka for real-time processing.

The role requires 2–5 years of relevant experience, strong communication with stakeholders, and a startup-mentality to thrive in a fast-growing data consultancy.

Formación

  • Bachelor’s degree in Computer Science or related field.
  • 2–5 years of experience as a Data Engineer.
  • Proficiency in Python and SQL and database management.
  • Experience with ETL pipelines and data integration.
  • Cloud services experience (Azure, GCP, AWS).
  • Experience with Spark and Kafka.
  • Strong communication and stakeholder collaboration skills.

Responsabilidades

  • Data Pipeline Development: build and optimise data pipelines across systems.
  • Database Management: ensure data integrity and efficient storage/retrieval.
  • Cloud Services Integration: leverage Azure, GCP, AWS for scalable solutions.
  • ML Integration: collaborate to embed ML models in pipelines.
  • Real-time processing: work with Spark and Kafka for analytics.

Conocimientos

Python
SQL
Database management
Data pipelines ETL
Cloud services (Azure, GCP, AWS)
ML modeling
Spark
Kafka

Educación

Bachelor’s degree in Computer Science
Bachelor’s degree in Electronics & Communication Engineering

Descripción del empleo

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.
The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact’s offers (and more): data marketing, data governance, strategy consulting, product owner…

What you will be doing?
As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data.

Your responsibilities will include:

  • Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms.
  • Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions.
  • Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions.
  • Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing.
  • Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics.

What we are looking for?

  • 2-5 years: Data Engineer
  • Proficiency in Python, SQL, and database management.
  • Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka.
  • Proven problem-solving skills and a solution-oriented mindset.
  • Experience working with business stakeholders either internally or externally
  • Excellent communication skills to collaborate effectively within teams and with stakeholders.
  • Strong business acumen with an interest in business-facing roles.
  • Adaptability and a start-up mentality to thrive in a dynamic environment.
  • Minimum of a bachelor’s degree in Computer Science, Electronics, and Communication Engineering degrees.

Artefact is the place to be: come and build the future of data and AI

Innovation: We have a passion for creating impacting projects and believe innovation can come from anyone.
Action: We make things rather than telling people how to make them.
Collaboration: We believe in bringing talented people together, winning together, and in learning from each other.

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