Data Engineer

4 weeks ago


delhi, 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 words to search for the candidate.
Mandatory – Snowflake, SQL, Python – Pandas, Data Modelling
Good to have but not mandatory – Healthcare Domain experience, AWS S3 & Blob
Job Description
Required Skills and Qualifications
Proficiency in Snowflake , with extensive experience in data warehouse architecture, management and Snowpipe.
Knowledge of User Defined Function vs Stored Procedure, Multi Clusters DWH, Views vs Secure Views & Materialized views in Snowflake.
Performance tuning and how to improve performance in Snowflake.
Expertise in SQL and database development , with the ability to write complex queries and optimize database performance.
Strong programming skills in Python , including experience with data libraries and frameworks, like Pandas .
Solid understanding of data modeling principles and best practices.
Strong communication and collaboration skills, with the ability to work in a team environment.
Bachelor’s or Master’s degree in computer science, Information Technology, or a related field.
Key Responsibilities
Design and implement robust, scalable data pipelines and architectures in Snowflake, optimizing data flow and collection for cross functional teams.
Develop complex SQL queries and scripts to support data transformation, aggregation, and analysis.
Utilize Python for automating data processes, integrating data systems, and building advanced analytics models.
Lead data modeling initiatives, ensuring the integrity and efficiency of data structures.
Collaborate with cross functional teams to understand data needs, gather requirements, and deliver data driven solutions that align with business goals.
Implement data security and compliance measures, adhering to industry standards and regulations.
Conduct data analysis and provide insights to support decision making and strategy development.
Stay abreast of emerging technologies and trends in data engineering, recommending, and implementing improvements to our data systems and processes.
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