Data Modeler/ETL Architect

Description :

Experience : 10-15 years

Location : Remote

Job Overview :

We are seeking a highly experienced Data Modeler / ETL Architect with deep expertise in data modeling, ETL design, and DBT (Data Build Tool) frameworks. Must have experience in Ecom and Order supply chain management. The ideal candidate will be responsible for designing, implementing, and optimizing scalable data models, pipelines, and data architecture to support enterprise-level analytics and data warehouse solutions.

Key Responsibilities :

- Design and maintain conceptual, logical, and physical data models for enterprise data platforms.

- Lead the architecture, development, and optimization of ETL/ELT workflows using DBT, SQL, and modern data integration tools.

- Must have experience in Ecom and Order Supply chain management domain

- Define and implement data modeling standards, best practices, and governance frameworks.

- Collaborate with data engineers, analysts, and business stakeholders to understand requirements and translate them into robust data solutions.

- Architect data pipelines that ensure data quality, integrity, and consistency across multiple systems.

- Optimize data models for performance, scalability, and re usability in analytical workloads (Snowflake, Redshift, BigQuery, etc.).

- Oversee data lineage, metadata management, and documentation to ensure transparency and maintainability.

- Provide technical leadership and mentorship to data engineers and analysts in data modeling and DBT development.

- Participate in data architecture reviews, performance tuning, and troubleshooting

Required Skills and Qualifications :

- 10+ years of overall experience in data engineering, data modeling, or data architecture.

- Expertise in ETL/ELT design and architecture using modern data integration platforms.

- Proficiency in SQL and experience with cloud data warehouses (e.g., Snowflake, Redshift, BigQuery, Azure Synapse).

- Hands-on experience with data modeling techniques (3NF, star schema, data vault, dimensional modeling).

- Solid understanding of data governance, data lineage, and data quality frameworks.

- Experience in cloud platforms (AWS, Azure, or GCP).

- Understanding of business intelligence (BI) and analytics tools such as Looker, Power BI, or Tableau.

- Familiarity with version control (Git), CI/CD for data pipelines, and agile development practices.

- Strong problem-solving, analytical, and communication skills.