Data Engineer
VIVADATA -
Riyadh, Saudi Arabia
Job Details
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Job Description
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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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.
APPLY NOW
Apply for this jobApply for this job
SHARE THIS OFFER
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Consulting
View more
Data Analytics
View more
Data Analytics (New)
View more
Data Consulting (New)
View more
Data Science
View more
Teamwork makes the dream works.
Artefact's teams are made up of the best experts in their fields, and it's our biggest responsibility to ensure their professional development and personal wellbeing.
LEARN MORE
Job Requirements
The role requires 2-5 years of experience in data engineering with proficiency in Python, SQL, and database management.
Candidates should have experience with ETL processes, cloud services, and machine learning integration.
Candidates should have experience with ETL processes, cloud services, and machine learning integration.
