Data Engineer - ETL
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Master-Works is looking for a talented Data Engineer - ETL to join our dynamic team. In this role, you will focus on designing, developing, and maintaining ETL processes that extract, transform, and load data from various sources into our data platforms. Your work will enable data accessibility for analytics and reporting, driving key business decisions.
Key Responsibilities:
ā¢ Design, develop, and implement robust ETL processes to ensure efficient data extraction, transformation, and loading.
ā¢ Collaborate with data analysts and business stakeholders to gather data requirements and translate them into technical specifications.
ā¢ Optimize ETL workflows for performance, scalability, and reliability.
ā¢ Monitor ETL processes to proactively identify and resolve data quality issues.
ā¢ Document ETL processes, data models, and architecture to ensure clear understanding and maintainability.
ā¢ Stay updated on emerging data technologies and best practices to recommend improvements to existing systems. Requirements
ā¢ Experience with ETL tools such as Informatica, Talend, and SSIS
ā¢ Proficient in programming languages such as Python, Java, Scala, or other relevant languages
ā¢ Strong skills in SQL and programming
ā¢ Ability to optimize ETL performance
ā¢ Experience with data integration techniques and tools to design efficient and scalable data architectures
ā¢ 6+ years of professional experience
Requirements
- ā¢Experience with ETL tools such as Informatica, Talend, and SSIS
- ā¢Proficient in programming languages such as Python, Java, Scala
- ā¢Strong skills in SQL and programming
- ā¢Ability to optimize ETL performance
- ā¢Experience with data integration techniques and tools
- ā¢6+ years of professional experience
Responsibilities
- ā¢Design, develop, and implement robust ETL processes
- ā¢Collaborate with data analysts and business stakeholders to gather data requirements
- ā¢Optimize ETL workflows for performance, scalability, and reliability
- ā¢Monitor ETL processes to proactively identify and resolve data quality issues
- ā¢Document ETL processes, data models, and architecture
- ā¢Stay updated on emerging data technologies and best practices
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