- Design and develop scalable reliable data platforms and pipelines for analytics and operations
- Implement data processing workflows using distributed frameworks (Apache Spark/pySpark Databricks)
- Evolve the organizations cloud data platform leveraging Azure technologies (Data Factory Synapse Event Hub Azure Data Lake Storage)
- Model data to support analytics reporting and downstream consumption
- Integrate and process data from multiple sources ensuring quality and consistency
- Monitor and optimize pipeline performance ensuring reliability and scalability
- Collaborate with analysts scientists and engineers to translate requirements into solutions
- Improve data engineering standards testing and operational reliability
- Evaluate and introduce new tools and technologies in the data engineering ecosystem
Qualifications :
- 3 years of hands-on experience in data engineering or building data processing platforms
- Strong SQL skills and solid Python experience for pipeline development
- Experience with distributed processing frameworks (Apache Spark/pySpark Databricks preferred)
- Practical experience designing and implementing pipelines in cloud environments (Azure preferred)
- Experience with production-scale analytical systems and data modeling
- Understanding of ETL/ELT design dimensional modeling and data warehousing principles
- Experience with modern data lake architectures and formats (Parquet JSON)
- Familiarity with workflow orchestration tools (Airflow)
- Experience with database development and optimization
- Ability to design scalable solutions with minimal supervision
- Strong collaboration and communication skills
- Professional proficiency in English
Remote Work :
Yes
Employment Type :
Full-time
Design and develop scalable reliable data platforms and pipelines for analytics and operationsImplement data processing workflows using distributed frameworks (Apache Spark/pySpark Databricks)Evolve the organizations cloud data platform leveraging Azure technologies (Data Factory Synapse Event Hub A...
- Design and develop scalable reliable data platforms and pipelines for analytics and operations
- Implement data processing workflows using distributed frameworks (Apache Spark/pySpark Databricks)
- Evolve the organizations cloud data platform leveraging Azure technologies (Data Factory Synapse Event Hub Azure Data Lake Storage)
- Model data to support analytics reporting and downstream consumption
- Integrate and process data from multiple sources ensuring quality and consistency
- Monitor and optimize pipeline performance ensuring reliability and scalability
- Collaborate with analysts scientists and engineers to translate requirements into solutions
- Improve data engineering standards testing and operational reliability
- Evaluate and introduce new tools and technologies in the data engineering ecosystem
Qualifications :
- 3 years of hands-on experience in data engineering or building data processing platforms
- Strong SQL skills and solid Python experience for pipeline development
- Experience with distributed processing frameworks (Apache Spark/pySpark Databricks preferred)
- Practical experience designing and implementing pipelines in cloud environments (Azure preferred)
- Experience with production-scale analytical systems and data modeling
- Understanding of ETL/ELT design dimensional modeling and data warehousing principles
- Experience with modern data lake architectures and formats (Parquet JSON)
- Familiarity with workflow orchestration tools (Airflow)
- Experience with database development and optimization
- Ability to design scalable solutions with minimal supervision
- Strong collaboration and communication skills
- Professional proficiency in English
Remote Work :
Yes
Employment Type :
Full-time
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