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Snowflake is seeking an Analytics Engineer to join the Finance Analytics Engineering team in Pune. This role focuses on building and maintaining the data infrastructure that powers financial reporting, analysis, and automation across the organization.
Key responsibilities include:
- Develop and maintain data infrastructure using SQL, Python, Snowflake, dbt, and Airflow within an agile framework
- Design and implement automated testing procedures for Snowflake data models
- Translate business requirements from Finance stakeholders into data model specifications
- Collaborate with IT and technical teams to source data from business systems and Snowflake databases
- Architect scalable, performant data models supporting diverse use cases and single sources of truth
- Contribute to data governance strategies, including permissions, security models, data lineage, and definitions
- Partner with Finance BI and technical leads on requirements definition, project planning, and user testing
- Create and maintain comprehensive documentation for data models and key metrics
- Identify and drive improvements in processes, data systems, and team workflows
Required qualifications:
- 3+ years as an analytics, data, or BI engineer
- Advanced SQL skills with experience building data infrastructure for large-scale relational datasets
- Python experience for data parsing, structuring, and transformation
- Hands-on experience with MPP databases (Snowflake, Redshift, BigQuery, or equivalent)
- Strong stakeholder communication and prioritization abilities
- Problem-solving mindset with attention to detail and quality
- Ability to work in fast-paced, dynamic environments
Preferred experience includes ERP/Financial Planning tools, CI/CD pipelines, agile methodologies, product finance support, SaaS cost attribution models, cloud cost management (FOCUS Framework), and cloud platforms (AWS, Azure, GCP).
The role requires in-person attendance at the Pune office at least 3 days per week. Snowflake is a global cloud data platform company serving customers worldwide, emphasizing AI-native thinking and experimental approaches to problem-solving.
