Role Overview :

We are seeking a seasoned Data Engineering professional to spearhead our data architecture initiatives and drive the evolution of our analytical ecosystem. In this role, you will be responsible for designing robust data models and optimizing our Snowflake-based data warehousing environment to support complex business intelligence needs. You will collaborate closely with cross-functional product teams, data scientists, and senior stakeholders to translate intricate business requirements into scalable, high-performance data pipelines. By architecting efficient storage and processing solutions, you will directly influence the speed and accuracy of decision-making across the organization, ensuring our data infrastructure remains a competitive asset in a fast-paced market.

Key Responsibilities :

- Architect and maintain complex data models that serve as the foundation for enterprise-wide reporting and advanced analytics, ensuring high data integrity and performance.

- Lead the end-to-end design and implementation of scalable ETL/ELT pipelines within the Snowflake environment to streamline data ingestion from disparate sources.

- Optimize Snowflake database performance by managing compute resources, clustering keys, and materialized views to reduce latency for end-users.

- Partner with business stakeholders to define data requirements, ensuring that the data warehouse architecture aligns with long-term strategic business objectives.

- Mentor junior data engineers and establish best practices for SQL development, code reviews, and version control to maintain high engineering standards across the team.

Required Skillset :

- Demonstrated expertise in designing conceptual, logical, and physical data models for large-scale data warehousing environments.

- Advanced proficiency in Snowflake DB architecture, including performance tuning, security configurations, and cost optimization strategies.

- Proven ability to write complex, highly optimized SQL queries and stored procedures to handle large-scale data transformations.

- Strong experience in building and maintaining robust ETL/ELT workflows using modern data engineering tools and frameworks.

- Exceptional communication skills with the ability to articulate technical concepts to non-technical stakeholders and influence project direction.

- A collaborative mindset with the ability to thrive in a hybrid work environment across Bangalore, Chennai, Pune, or Mumbai.

- A Bachelors or Masters degree in Computer Science, Information Systems, or a related quantitative field is preferred.

- Candidates must possess 8 to 12 years of relevant professional experience in data engineering and warehousing roles.