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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.
- 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.
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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