Data Engineer - ETL/Snowflake DB (5-7 yrs)

Responsibilities :

- Design, develop, and implement efficient data pipelines using Snowflake as the data warehouse.

- Utilize Python for data engineering tasks, including data extraction, transformation, and loading (ETL) processes.

- Leverage AWS data engineering tools (e.g , AWS Glue, S3) to automate data ingestion and orchestrate workflows.

- Ensure data quality and consistency through data cleansing, transformation, and validation techniques.

- Build and maintain robust data models that optimize query performance and support complex data analysis.

- Write clean, efficient, and maintainable code, adhering to best practices for data engineering.

- Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and translate them into technical solutions.

- Monitor and troubleshoot data pipelines to identify and resolve issues proactively.

- Stay up-to-date with the latest advancements in Snowflake, Python data engineering libraries, and cloud data warehousing best practices.

Qualifications :

- Minimum of 5+ years of experience as a Data Engineer or a similar role.

- In-depth knowledge of Snowflake data warehousing concepts, including data loading, querying, and performance optimization.

- Proficiency in Python for data manipulation and scripting, with experience in data engineering libraries (e.g , Pandas).

- Solid understanding of ETL processes, data transformation techniques, and data modeling principles.

- Experience with AWS data engineering tools (e.g , AWS Glue, S3) a plus.

- Experience with dbt or other data transformation tools (a plus).

- Strong analytical and problem-solving skills with the ability to identify and resolve data quality issues.

- Excellent communication, collaboration, and interpersonal skills