Key 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.
Required Skills & Experience
· 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.
Good to Have
· 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.
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