- Architect, develop, and optimize complex SQL-based data pipelines and transformations in Snowflake.

- Lead the design and implementation of dimensional and analytical data models aligned to business requirements.

- Drive adoption of dbt (preferred) or similar transformation frameworks for standardized modeling, testing, and documentation.

- Own performance tuning, cost optimization, and scalability of Snowflake workloads.

- Define and enforce data engineering best practices, coding standards, and review processes.

- Design and manage orchestration workflows using Airflow, Dagster, or equivalent tools.

- Implement and govern CI/CD pipelines, version control, and automated deployments for data assets.

- Partner with business stakeholders to translate complex requirements into robust technical solutions.

- Lead troubleshooting, root-cause analysis, and proactive reliability improvements across data pipelines.

- Actively participate in Agile ceremonies and provide technical leadership within delivery teams.

- Mentor and guide junior and mid-level data engineers.

Required Skills :

- Advanced SQL expertise (5+ years) with proven experience in complex transformations, optimization, and large-scale datasets.

- Strong hands-on experience with Snowflake, including performance tuning and cost-efficient design.

- Deep understanding of data modeling techniques (dimensional modeling, fact/dimension design, analytics schemas).

- Experience designing and maintaining enterprise-grade data pipelines.

- Strong exposure to Agile delivery models and cross-functional collaboration.

- Solid understanding of CI/CD processes and tools (GitHub, GitLab, Azure DevOps, etc.).

- Experience with workflow orchestration platforms such as Airflow, Dagster, or similar