Job Description

Key Responsibilities:

Design, develop, and maintain scalable ETL/ELT pipelines in

Snowflake

to support data migration from legacy systems. Leverage

Python

for data transformation, automation, and orchestration of migration workflows. Optimize and refactor complex

SQL queries

to ensure efficient data processing and reporting in Snowflake. Collaborate on

data modeling and schema design

to align with Snowflake architecture and performance best practices. Monitor and troubleshoot data pipeline performance during and after migration phases. Work closely with data analysts, scientists, and business stakeholders to ensure accurate and timely data delivery. Implement and enforce

data governance, security policies

, and access controls within Snowflake. Collaborate with DevOps teams to integrate data engineering workflows into broader CI/CD frameworks.

Required Skills:

4-6 years of experience in

data engineering

, with proven expertise in

Snowflake

and

Python

. Strong command of

Snowflake features

such as scripting, time travel, virtual warehouses, and query optimization. Hands-on experience with

ETL tools

, data integration strategies, and migration methodologies. Solid understanding of

data warehousing principles

, normalization techniques, and performance optimization. Familiarity with

cloud platforms

(AWS, Azure, or GCP) and orchestration tools. Excellent problem-solving skills and ability to work independently in a dynamic, fast-paced environment. Understanding of version control systems, particularly Git, including branching, merging, and pull request workflows Experience with Snowflake advanced features including Snowpipe, Streams, Tasks, and Stored Procedures. Familiarity with ETL orchestration tools such as Airflow, DBT, or Matillion. * Ability to work with semi-structured data formats like JSON and Parquet.