Data Engineer

Role Overview

We are seeking a skilled Snowflake Data Engineer responsible for designing, developing, and maintaining scalable data pipelines and data engineering solutions using modern cloud data technologies. The ideal candidate should have strong hands-on experience with Snowflake, Python, SQL, PySpark, DBT, and ETL, along with a good understanding of AI/ML concepts and their application in data engineering environments.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Develop efficient and optimized data solutions using Snowflake.
• Write complex and performance-optimized SQL queries, stored procedures, views, and data transformations.
• Develop data processing applications using Python and PySpark.
• Build and maintain transformation workflows using DBT.
• Perform data ingestion, transformation, cleansing, validation, and integration across multiple source systems.
• Optimize Snowflake queries, warehouses, tables, and data models for performance and cost efficiency.
• Participate in the development and integration of AI/ML-enabled data solutions.

Requirements

• Strong hands-on experience with Snowflake.
• Strong Python programming/scripting skills.
• Advanced SQL and query optimization.
• Hands-on experience with large-scale data processing using PySpark.
• Experience with DBT for data transformation and modeling.
• Strong understanding of ETL/ELT implementation.
• Understanding of AI/ML concepts and data pipelines for AI/ML.

Skills

• Snowflake
• Python
• SQL
• PySpark
• DBT

Nice to Have

• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with Airflow or other workflow orchestration tools.
• Knowledge of Data Warehousing and Data Modeling concepts.
• Experience with CI/CD, Git, and DevOps practices.
• Experience in Generative AI, LLMs, RAG, or vector databases.