Artefact

Data and AI-driven business transformation consulting

Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Full-timeBeirut, LebanonNo salary listedIn-person

About the Job

Requirements

Proficiency in Python, SQL, and database management.
Experience with data pipeline ETL, cloud services (Microsoft Azure and Google Cloud Platform are preferred), machine-learning modeling, Spark, and Kafka.
Candidates should have problem-solving ability and a solution-oriented mindset.
Candidates should be able to collaborate with teams and stakeholders.
Candidates should have business acumen and an interest in business-facing roles.
Candidates should be adaptable and able to work in a start-up environment.
Candidates with similar skill sets and experience have often succeeded in technology or consultancy firms.

Responsibilities

Build and optimise data pipelines to facilitate data flow across systems and platforms.
Manage databases, ensure their integrity, and implement data storage and retrieval solutions.
Use cloud services such as Microsoft Azure, Google Cloud Platform, and Amazon Web Services to architect and deploy scalable data solutions.
Collaborate with teams to integrate machine-learning models into data pipelines for enhanced data processing.
Implement and work with Spark and Kafka for real-time data processing and analytics.

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?

Proficiency in Python, SQL, and database management.
Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP preferred), ML Modeling, Spark & Kafka.
Proven problem-solving skills and a solution-oriented mindset.
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.
Candidates with similar skill sets and experiences have excelled in technology firms or consultancy firms.
Successful candidates often possess Computer Science, Electronics, and Communication Engineering degrees.

About the Company

Artefact

Data and AI-driven business transformation consulting

Artefact helps organizations use data and AI to transform their operations and decision-making. It provides end-to-end services across the data value chain, from strategy and data platform implementation to governance, advanced analytics, and sector-specific AI tools, delivered through consulting and project execution. The company works with industries like FMCG, retail, and luxury goods to optimize marketing performance, customer engagement, and ROI. Artefact differentiates itself by combining consulting expertise with data science and AI capabilities across multiple regions, offering integrated, sector-focused solutions rather than just advisory services. The main goal is to help clients adopt data-driven approaches to improve efficiency, decision quality, and marketing results at scale.

Company size: 1,001-5,000
Company stage: IPO
Headquarters: Paris, France
Founded: 1998

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