Data Engineer

2 weeks ago


India Response Informatics Full time

Working Hours: 2pm to 11pm IST

Band: U3 or U4

Working Location: Remote - PAN INDIA

Experience: 6-12 Years

Key phrases for finding the right candidate.

  • Mandatory – Snowflake, SQL, Python – Pandas, Data Modelling
  • Desirable but not obligatory – Healthcare Domain experience, AWS S3 & Blob

Job Summary

Required Abilities and Credentials

  • Proficiency in Snowflake, with extensive expertise in data warehouse architecture, management, and Snowpipe.
  • Understanding of User Defined Function vs Stored Procedure, Multi Clusters DWH, Views vs Secure Views & Materialized views in Snowflake.
  • Performance enhancement and strategies to boost performance in Snowflake.
  • Proficient in SQL and database development, capable of constructing intricate queries and enhancing database performance.
  • Solid programming skills in Python, including familiarity with data libraries and frameworks, such as Pandas.
  • Thorough comprehension of data modeling principles and best practices.
  • Effective communication and teamwork skills, with the capability to function in a team environment.
  • Bachelor's or Master's degree in computer science, Information Technology, or a relevant field.

Main Responsibilities

  • Devising and implementing resilient, expandable data pipelines and architectures in Snowflake, enhancing data flow and collection for cross-functional teams.
  • Creating intricate SQL queries and scripts to facilitate data transformation, aggregation, and analysis.
  • Using Python to automate data processes, integrate data systems, and establish advanced analytics models.
  • Leading data modeling efforts to ensure data structure integrity and efficiency.
  • Collaborating with cross-functional teams to grasp data requirements, gather specifications, and deliver data-driven solutions that align with business objectives.
  • Implementing data security and compliance procedures in compliance with industry standards and regulations.
  • Conducting data analysis and offering insights to bolster decision-making and strategy formation.
  • Remaining updated on emerging data engineering technologies and trends, suggesting and executing enhancements to our data systems and processes.

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