- Design and implement scalable data pipelines to process large volumes of telecom data;
- Develop and optimize ETL processes for efficient data integration and transformation;
- Collaborate with data scientists to deploy machine learning models in production environments;
- Create and maintain data warehouses and data lakes to support analytics and ML/AI initiatives;
- Implement data quality checks and monitoring systems to ensure data integrity;
- Develop APIs and services to expose data and ML/AI capabilities to other teams;
- Optimize data storage and retrieval systems for improved performance;
- Participate in the evaluation and implementation of new data technologies and tools;
- Contribute to the development of best practices for data engineering and ML/AI operations;
- Provide technical guidance and mentorship to junior team members.
Qualifications :
- Bachelors or Masters degree in Computer Science Data Science or a related field;
- 3 years of experience in data engineering with a focus on ML/AI applications;
- Strong programming skills in Python Java or Scala;
- Extensive experience with big data technologies such as Hadoop Spark and Hive;
- Proficiency in SQL and NoSQL databases;
- In-depth knowledge of machine learning and AI algorithms;
- Familiarity with cloud platforms (AWS Azure or GCP) and their data services;
- Experience with data visualization tools and techniques;
- Relevant certifications in data engineering or cloud platforms (e.g. AWS Certified Data Analytics) are a plus.
Additional Information :
The Devoteam Group works for equal opportunities promoting its employees based on merit and actively fights against all forms of discrimination. We are convinced that diversity contributes to the creativity dynamism and excellence of our organization. All of our vacancies are open to people with disabilities.
Remote Work :
No
Employment Type :
Full-time
Design and implement scalable data pipelines to process large volumes of telecom data;Develop and optimize ETL processes for efficient data integration and transformation;Collaborate with data scientists to deploy machine learning models in production environments;Create and maintain data warehouses...
- Design and implement scalable data pipelines to process large volumes of telecom data;
- Develop and optimize ETL processes for efficient data integration and transformation;
- Collaborate with data scientists to deploy machine learning models in production environments;
- Create and maintain data warehouses and data lakes to support analytics and ML/AI initiatives;
- Implement data quality checks and monitoring systems to ensure data integrity;
- Develop APIs and services to expose data and ML/AI capabilities to other teams;
- Optimize data storage and retrieval systems for improved performance;
- Participate in the evaluation and implementation of new data technologies and tools;
- Contribute to the development of best practices for data engineering and ML/AI operations;
- Provide technical guidance and mentorship to junior team members.
Qualifications :
- Bachelors or Masters degree in Computer Science Data Science or a related field;
- 3 years of experience in data engineering with a focus on ML/AI applications;
- Strong programming skills in Python Java or Scala;
- Extensive experience with big data technologies such as Hadoop Spark and Hive;
- Proficiency in SQL and NoSQL databases;
- In-depth knowledge of machine learning and AI algorithms;
- Familiarity with cloud platforms (AWS Azure or GCP) and their data services;
- Experience with data visualization tools and techniques;
- Relevant certifications in data engineering or cloud platforms (e.g. AWS Certified Data Analytics) are a plus.
Additional Information :
The Devoteam Group works for equal opportunities promoting its employees based on merit and actively fights against all forms of discrimination. We are convinced that diversity contributes to the creativity dynamism and excellence of our organization. All of our vacancies are open to people with disabilities.
Remote Work :
No
Employment Type :
Full-time
View more
View less