Responsible for designing, developing and maintaining robust data solutions that integrate Snowflake Data Warehouse and ETL tools. This role involves managing end-to-end data pipelines, optimizing Snowflake performance and collaborating with cross-functional teams to ensure data accuracy, security and efficiency. The role requires transforming data to provide business insights, guiding best practices and optimizing workflows in a cloud-based environment.
Job Responsibilities- Design and develop data architectures, data pipelines and ETL processes using Snowflake and leading ETL tools (Informatica etc.).
- Manage data integration workflows between multiple data sources and the Snowflake Data Cloud.
- Optimize Snowflake performance, ensuring proper use of storage, query optimization and scaling for large datasets.
- Implement data security, governance and compliance measures within the Snowflake platform.
- Collaborate with stakeholders, including data analysts, data engineers and business units, to translate business requirements into data solutions.
- Perform data modeling and design, including Star and Snowflake schemas, to support business intelligence and analytics initiatives.
- Monitor and troubleshoot ETL processes, ensuring high data quality and availability.
- Lead data migration projects, including legacy system integration with Snowflake.
- Provide technical guidance and mentorship to team members on Snowflake and ETL best practices.
- Task Management – Basic level of project management knowledge and experience. Should be able to plan tasks, discuss and work on priorities. o
- Communication – Able to convey ideas and information clearly and accurately to self or others whether in writing or verbal.
Education BE/B.TechMaster of Computer ApplicationWork Experience- Minimum of 0-5 years of relevant experience in Pharma domain.
- 6+ years of experience in data engineering, with a focus on ETL development and data warehousing.
- 3+ years of hands-on experience with Snowflake.
- Proven expertise in working with ETL tools such as Informatica or equivalent.
- Experience in cloud-based data architecture (AWS / Azure / Google Cloud).
- Experience with SQL, PL/SQL and scripting languages like Python or Shell for automation and orchestration.
- Experience in managing large datasets, data migration and real-time data processing.