Snowflake Data Engineer

Fugetron Corporation; Mumbai; Hybrid; INR 1,500,000 - 3,000,000; Full time

Job summary

Fugetron Corporation is seeking a skilled Snowflake Engineer with 5+ years of hands-on Snowflake experience and strong Python and SQL skills. The role focuses on building and optimizing data pipelines using modern cloud architectures.

Responsibilities include designing ETL/ELT pipelines, writing efficient SQL, migrating data to Snowflake, and optimizing data models. Collaboration with analysts and engineers is essential to meet data requirements and ensure data quality.

Qualifications

• Bachelors degree in Computer Science, Information Technology, or related field.
• 4+ years of Snowflake experience, including Snowflake SQL, SnowSQL, Snowpipe, Snowpark, Streams, and Tasks.
• Strong Python skills for data manipulation and automation.
• Advanced SQL skills for complex queries and stored procedures.
• Experience with data pipeline orchestration tools (Airflow, DBT, Prefect).
• Familiarity with AWS/GCP/Azure and cloud storage (S3, GCS).
• Proven experience in data migration projects.
• Understanding of data warehousing concepts.

Responsibilities

• Design, develop, and maintain ETL/ELT pipelines using Snowflake and Python.
• Write efficient SQL queries for data extraction, transformation, and reporting.
• Migrate data from on-prem or other cloud databases to Snowflake with minimal downtime.
• Optimize Snowflake data models, including schema design, clustering, and performance tuning.
• Collaborate with stakeholders to translate data requirements into technical solutions.
• Integrate data from APIs, flat files, cloud storage, and relational databases.
• Implement data quality checks and monitoring for reliability.
• Maintain documentation for pipelines, schema changes, and processes.

Skills

Snowflake

Python

SQL

ETL/ELT pipelines

Data migration

Data warehousing concepts

Cloud platforms

Airflow

DBT

Prefect

Education

Bachelor's degree in Computer Science/Information Technology or related field

Tools

Airflow

DBT

Prefect

Job description

We are seeking a highly skilled Snowflake Engineer with at least 5 years of hands-on experience in Snowflake, and a strong command of Python and SQL. The ideal candidate will be responsible for building and optimizing data pipelines, transforming complex data sets, and enabling efficient data storage and access using modern cloud-based data architectures.

Key Responsibilities:

• Design, develop, and maintain scalable and robust ETL/ELT pipelines using Snowflake and Python.
• Write efficient SQL queries for data extraction, transformation, and reporting.
• Perform end-to-end data migration from on-prem or other cloud databases (e.g., Oracle, SQL Server, MySQL, Redshift) to Snowflake, ensuring minimal downtime and data integrity.
• Optimize Snowflake data models, including schema design, clustering, and query performance tuning.
• Work with stakeholders to understand data requirements and translate them into technical solutions.
• Integrate data from multiple sources including APIs, flat files, cloud storage, and relational databases.
• Implement data quality checks and monitoring to ensure data reliability and integrity.
• Collaborate with Data Analysts, Scientists, and Engineers on cross-functional data initiatives.
• Maintain documentation for data pipelines, schema changes, and processes.

Required Skills & Qualifications:

• Bachelors degree in Computer Science, Information Technology, or related field.
• 4+ years of experience working with Snowflake, including hands-on usage of Snowflake SQL, SnowSQL, Snowpipe, Snowpark, Streams, Tasks, and performance optimization.
• Strong Python skills for data manipulation and automation.
• Advanced SQL skills with the ability to write complex queries and stored procedures.
• Experience with data pipeline orchestration tools (e.g., Airflow, DBT, Prefect, etc.).
• Familiarity with cloud platforms (AWS/GCP/Azure) and cloud storage systems (S3, GCS, etc.).
• Proven experience in data migration projects, including strategy, execution, and validation.
• Understanding of data warehousing concepts and best practices.