Role : Senior Data Engineer Transformations & dbt (Immediate joiners) :

Location : Remote.

Experience : 08 to 12 Years.

Joining requirement : Immediate joiner preferred.

Employment Type : Full-Time.

Client Environment : US-based Enterprise Data Platform.

Role Overview :

We are looking for a Senior Data Engineer Transformations & dbt (57 Years Experience) to join a Snowflake-centric enterprise data platform team. This role is deeply hands-on and focuses on transforming raw Snowflake data into trusted, analytics-ready datasets using advanced SQL and dbt best practices. You will own data modeling standards, transformation reliability, and data quality, while collaborating closely with analytics engineers, SQL developers, and US-based stakeholders. This is not a support role. We are looking for someone who has built and owned production-grade transformation pipelines in real-world enterprise environments.

Key Responsibilities :

1. Data Transformation & dbt Ownership :

- Design, develop, and maintain dbt-based transformation pipelines.

- Own fact and dimension data modeling, including :

1. Incremental models.

2. Slowly Changing Dimensions (SCD).

3. Aggregations and rollups.

- Establish and enforce dbt project structure, naming conventions, and modeling standards.

- Manage transformation dependencies and execution ordering.

2. Data Quality & Trust :

- Implement dbt tests, validations, and reconciliation checks.

- Ensure metric definitions are consistent, accurate, and trusted.

- Proactively identify and resolve data quality issues.

- Align transformed data with upstream source systems and business rules.

3. Snowflake Optimization :

- Optimize SQL transformations for performance and cost.

- Tune Snowflake warehouse usage for transformation workloads.

- Reduce unnecessary compute usage through efficient SQL and dbt design.

4. Analytics Enablement :

- Deliver clean, well-documented datasets for BI tools and analytics engineers.

- Ensure datasets are semantic-ready for reporting and dashboards.

- Support downstream analytics and visualization teams.

5. Engineering Excellence :

- Follow Git-based development workflows.

- Participate in CI/CD pipelines (Git, Jenkins, etc.).

- Conduct peer code reviews.

- Maintain documentation, data lineage, and transformation logic.

- Mentor mid-level and junior engineers where required.

Requirements :

1. Experience :

- 5 to d7 years of experience in Data Engineering, Data Transformation, or Analytics Engineering.

- Proven experience working with enterprise-scale data platforms.

2. Required Skills :

- Advanced SQL (Snowflake).

- Strong hands-on experience with dbt.

- Solid understanding of Snowflake architecture and data modeling.

- Experience building analytics-ready datasets in production environments.

- Strong communication skills (verbal and written English).

Benefits :

1. Perks & Benefits :

- Work on a US enterprise-grade data platform.

- Long-term engagement with stable scope.

- Exposure to advanced Snowflake and dbt workloads.

- Clear role ownership and accountability.

- Strong engineering culture with documentation and best practices.