On-Site
Full-Time
Pune, Maharashtra
India
About the Role
Agivant is seeking a talented and passionate Senior Data Engineer to join our growing data team. In this role, you will play a key part in building and scaling our data infrastructure, enabling data-driven decision-making across the organization. You will be responsible for designing, developing, and maintaining efficient and reliable data pipelines for both ELT (Extract, Load, Transform) and ETL (Extract, Transform, Load) processes.
Responsibilities:
Design, develop, and maintain robust and scalable data pipelines for ELT and ETL processes, ensuring data accuracy, completeness, and timeliness.
Work with stakeholders to understand data requirements and translate them into efficient data models and pipelines.
Build and optimize data pipelines using a variety of technologies, including Elastic Search, AWS S3, Snowflake, and NFS.
Develop and maintain data warehouse schemas and ETL/ELT processes to support business intelligence and analytics needs.
Implement data quality checks and monitoring to ensure data integrity and identify potential issues.
Collaborate with data scientists and analysts to ensure data accessibility and usability for various analytical purposes.
Stay current with industry best practices, CI/CD/DevSecFinOps, Scrum and emerging technologies in data engineering.
Contribute to the development and enhancement of our data warehouse architecture
Requirements
Mandatory
Bachelor's degree in Computer Science, Engineering, or a related field
5+ years of experience as a Data Engineer with a strong focus on ELT/ETL processes
At least 3+ years of exp in Snowflake data warehousing technologies
At least 3+ years of exp in creating and maintaining Airflow ETL pipelines
Minimum 3+ years of professional level experience with Python languages for data manipulation and automation
Working experience with Elastic Search and its application in data pipelines
Proficiency in SQL and experience with data modelling techniques
Strong understanding of cloud-based data storage solutions such as AWS S3
Experience working with NFS and other file storage systems
Excellent problem-solving and analytical skills
Strong communication and collaboration skills
.
Responsibilities:
Design, develop, and maintain robust and scalable data pipelines for ELT and ETL processes, ensuring data accuracy, completeness, and timeliness.
Work with stakeholders to understand data requirements and translate them into efficient data models and pipelines.
Build and optimize data pipelines using a variety of technologies, including Elastic Search, AWS S3, Snowflake, and NFS.
Develop and maintain data warehouse schemas and ETL/ELT processes to support business intelligence and analytics needs.
Implement data quality checks and monitoring to ensure data integrity and identify potential issues.
Collaborate with data scientists and analysts to ensure data accessibility and usability for various analytical purposes.
Stay current with industry best practices, CI/CD/DevSecFinOps, Scrum and emerging technologies in data engineering.
Contribute to the development and enhancement of our data warehouse architecture
Requirements
Mandatory
Bachelor's degree in Computer Science, Engineering, or a related field
5+ years of experience as a Data Engineer with a strong focus on ELT/ETL processes
At least 3+ years of exp in Snowflake data warehousing technologies
At least 3+ years of exp in creating and maintaining Airflow ETL pipelines
Minimum 3+ years of professional level experience with Python languages for data manipulation and automation
Working experience with Elastic Search and its application in data pipelines
Proficiency in SQL and experience with data modelling techniques
Strong understanding of cloud-based data storage solutions such as AWS S3
Experience working with NFS and other file storage systems
Excellent problem-solving and analytical skills
Strong communication and collaboration skills
.