Data Architecture & Modeling: Design and implement scalable data models, including star and snowflake schemas, to support business intelligence and analytics.
ETL Development: Develop and maintain ETL pipelines using Snowflake features like Snowpipe, Tasks, and Streams to ingest, transform, and load data from various sources.
Performance Optimization: Optimize queries and data structures for performance and cost efficiency, ensuring fast and reliable data processing.
Collaboration: Work closely with data architects, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
Security & Compliance: Implement and maintain data security measures, including access controls and data encryption, to ensure compliance with organizational policies and regulations.
Career Growth: Clear progression from Senior Developer → Lead Data Engineer → Data Architect → Head of Data/CTO roles.
Skill Enhancement: Opportunities to gain expertise in Snowflake, cloud platforms (AWS, Azure, GCP), ETL tools, and data analytics.
Certifications: Companies often sponsor Snowflake, AWS, or Azure certifications to strengthen professional credentials.
Health Insurance: Coverage for employee and dependents, including hospitalization.
Life & Accidental Insurance: Protection in case of emergencies.
Wellness Programs: Yoga sessions, gym reimbursements, or mental health support in larger organizations.
Competitive Salary: Higher-than-average pay in IT and data engineering fields.
Performance Bonuses: Annual or quarterly incentives based on individual or team performance.
Provident Fund (PF) & Gratuity: Retirement benefits as per Indian labor law.
Stock Options / ESOPs: Sometimes offered in product or startup companies.