Data Engineer
Artefact Open At a glance
Mid-level Data Engineering role at Artefact. Beirut · full-time.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and tune pipelines that move data between systems, using Python and SQL for extraction, transformation and loading
- Maintain databases, protect data integrity and develop ways to store and retrieve information
- Use Azure, GCP or AWS to design and deploy data solutions that can scale
- Work with teams to place machine-learning models in pipelines and use Spark and Kafka for real-time processing
What you bring
- You’re proficient in Python, SQL and database management
- You have experience with ETL pipelines, cloud platforms, machine-learning modeling, Spark and Kafka
- You bring problem-solving ability, clear communication and an interest in business-facing work
Who this fits
This role suits a mid-level data engineer who can collaborate with teams and stakeholders and is interested in business-facing work. The listing notes that successful candidates often have a degree in computer science or a related engineering field.
From the employer
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.
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Data Engineering
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