Overview

We are looking for an experienced Senior Data Engineer with 8+ years of experience in Data Engineering, specializing in Snowflake, SQL, and dbt. The ideal candidate should possess strong expertise in designing and building scalable data pipelines, optimizing data warehouses, and implementing modern ELT solutions.

The candidate should have excellent SQL skills, hands-on experience with Snowflake architecture and performance optimization, strong knowledge of dbt, and exposure to cloud platforms (AWS/Azure/GCP). Experience with Python and modern data engineering practices is highly preferred.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Snowflake and dbt.
• Develop optimized SQL queries, stored procedures, views, and data models.
• Build and manage ELT workflows for data transformation and integration.
• Optimize Snowflake performance, warehouse utilization, and query execution.
• Implement data quality checks, testing, and monitoring within dbt.
• Work with business and technical teams to understand data requirements.
• Support cloud-based data platform development and modernization initiatives.
• Follow best practices for code quality, version control, and deployment.
• Troubleshoot production issues and recommend performance improvements.
• Mentor junior engineers and participate in technical design discussions.

Required Skills

Mandatory

• 8+ years of experience in Data Engineering.
• Strong expertise in SQL with excellent query optimization skills.
• Hands-on experience with Snowflake.
• Strong knowledge of dbt (Models, Sources, Tests, Snapshots, Macros, Incremental Models).
• Experience designing scalable Data Warehouse solutions.
• Strong understanding of Data Modeling (Star Schema, Snowflake Schema, Dimensional Modeling).
• Experience building ETL/ELT pipelines.
• Knowledge of Git and CI/CD practices.
• Excellent problem-solving and analytical skills.

Good to Have

• Experience with Python.
• Knowledge of cloud platforms (AWS, Azure, or GCP).
• Experience with data orchestration tools (Airflow or similar).
• Exposure to APIs and semi-structured data (JSON, Parquet).
• Snowflake or Cloud certifications.