ETL Developer Lead / Lead Data Engineer

As a Data Engineering Lead, you will play a crucial role in designing, developing, and optimizing scalable ETL pipelines using Talend. Your responsibilities will include architecting and managing high-performance data systems on cloud-based platforms such as Snowflake. You will also be expected to develop, test, and optimize advanced SQL scripts for data extraction, transformation, and loading into Data Warehouses.

Key Responsibilities:

• Ensure seamless data integration from multiple source systems into centralized DWH environments while upholding data quality and integrity.
• Drive performance tuning and optimization of data workflows to enhance efficiency and reduce latency.
• Automate data processes and implement best practices in data engineering.
• Collaborate with business analysts, data scientists, and stakeholders to deliver scalable data solutions.
• Mentor and guide junior data engineers on tools, architecture, and best practices.
• Troubleshoot and resolve complex data architecture and pipeline issues.

Qualifications Required:

• Proficiency in snowflake, Data Warehousing, ETL Development, Data Integration, SQL, Talend, and Data Modeling.
• Experience ranging from 7 to 15 years.

Stay abreast of emerging data engineering technologies and methodologies to ensure that you are at the forefront of innovation in the field. As a Data Engineering Lead, you will play a crucial role in designing, developing, and optimizing scalable ETL pipelines using Talend. Your responsibilities will include architecting and managing high-performance data systems on cloud-based platforms such as Snowflake. You will also be expected to develop, test, and optimize advanced SQL scripts for data extraction, transformation, and loading into Data Warehouses.

Key Responsibilities:

• Ensure seamless data integration from multiple source systems into centralized DWH environments while upholding data quality and integrity.
• Drive performance tuning and optimization of data workflows to enhance efficiency and reduce latency.
• Automate data processes and implement best practices in data engineering.
• Collaborate with business analysts, data scientists, and stakeholders to deliver scalable data solutions.
• Mentor and guide junior data engineers on tools, architecture, and best practices.
• Troubleshoot and resolve complex data architecture and pipeline issues.

Qualifications Required:

• Proficiency in snowflake, Data Warehousing, ETL Development, Data Integration, SQL, Talend, and Data Modeling.
• Experience ranging from 7 to 15 years.

Stay abreast of emerging data engineering technologies and methodologies to ensure that you are at the forefront of innovation in the field.