Overview

Key Responsibilities

Responsibilities

• Lead the design, development, and optimization of data pipelines and data warehouse solutions on Snowflake.
• Develop and maintain dbt models for data transformation, testing, and documentation.
• Collaborate with cross-functional teams including data architects, analysts, and business stakeholders to deliver robust data solutions.
• Ensure high standards of data quality, governance, and security across pipelines and platforms.
• Leverage Airflow (or other orchestration tools) to schedule and monitor workflows.
• Integrate data from multiple sources using tools like Fivetran.
• Provide technical leadership, mentoring, and guidance to junior engineers in the team.
• Optimize costs, performance, and scalability of cloud-based data environments.
• Contribute to architectural decisions, code reviews, and best practices.

Qualifications

• 8–12 years of overall experience in Data Engineering, with at least 3–4 years in a lead role.
• Strong hands-on expertise in Snowflake (data modeling, performance tuning, query optimization, security, and cost management).
• Proficiency in dbt (core concepts, macros, testing, documentation, and deployment).
• Solid programming skills in Python (for data processing, automation, and integrations).
• Experience with workflow orchestration tools such as Apache Airflow.
• Exposure to ELT/ETL tools like Fivetran.
• Strong understanding of modern data warehouse architectures, data governance, and cloud-native environments.
• Excellent problem-solving, communication, and leadership skills.
• Hands-on experience with Databricks (PySpark, Delta Lake, MLflow).
• Exposure to other cloud platforms (AWS, Azure, or GCP).
• Experience in building CI/CD pipelines for data workflows.