Data Analytics Manager - Snowflake

Vollzeit
Noida, Uttar Pradesh, India
vor 7 Monate

About HashiCorp:

HashiCorp is a fast-growing company that solves development, operations, and security challenges in infrastructure so organizations can focus on business-critical tasks. We build products to give organizations a consistent way to manage their move to cloud-based IT infrastructures for running their applications. Our products enable companies large and small to mix and match AWS, Microsoft Azure, Google Cloud, and other clouds as well as on-premises environments, easing their ability to deliver new applications for their business.

We are looking for an experienced Data Analyst to be part of the Financial Planning & Analysis (FP&A) Digitization team.

Education

  • Bachelor's Degree in Engineering or Science
  • Snowflake certified professional 

Experience 

  • Overall experience of 4+ years as Data Analyst. Minimum 2+ years experience on Snowflake.

What You Will Do:

1. Maintenance/Support: 

  • Work closely with the Business Intelligence (BI) team to deliver processed and refined data for integration into BI systems from the FP&A datamart on Snowflake.
  • Collaborate on the development of dashboards, providing the necessary backend data structures to support insightful visualizations.
  • Troubleshoot and optimize SQL queries for enhanced dashboard performance and responsiveness.
  • Run refresh of tables and views to provide updated feed to other systems or tools like Tableau and Anaplan.
  • Test updates to the data feed to/from other systems.

2. Database Schema, Table, and Views Management:

  • Create/update schemas, tables, and views on data mart as per business requirements.
  • Manage schemas, tables, and views to facilitate simplified and efficient data access for various analytical needs while ensuring data integrity. 

3. SQL Query Development:

  • Write and optimize stored procedures, ensuring seamless execution for efficient data retrieval and processing.
  • Develop SQL queries incorporating table Joins subqueries, and aggregations to extract data from diverse datasets.
  • Collaborate with cross-functional teams to understand data requirements and translate them into effective SQL queries.

4. Data Processing:

  • Handle data from multiple schemas and tables, SQL transformations to clean, filter, and aggregate information as needed.
  • Use data processing techniques to prepare datasets for further analysis and reporting.
  • Ensure data consistency and accuracy through rigorous validation processes. #LI-SG1 #LI-Hybrid

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