Lead Data Engineer

- Strong understanding of ETL/ELT fundamentals and best practices - Proficiency in Python for data engineering and automation tasks - Administration of Snowflake warehouses, databases, schemas, and role-based security

- Administer and manage Snowflake data warehouses, including databases, schemas, roles, and security configurations to ensure robust data governance - Optimize complex SQL queries and warehouse performance, reducing processing times and improving storage utilization - Manage and integrate AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch to build and maintain reliable cloud data infrastructure

Required Skills: - Advanced proficiency in SQL (basic and advanced) - Expertise in developing and managing dbt models, macros, and tests

Job requirements Experience Range: 8- 10 years of experience in data engineering, with hands-on expertise in Snowflake, dbt, and AWS cloud services Key Responsibilities: - Develop, maintain, and optimize dbt models, macros, and tests to support scalable ETL/ELT data pipelines

- Optimize complex SQL queries and warehouse performance, reducing processing times and improving storage utilization - Manage and integrate AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch to build and maintain reliable cloud data infrastructure - Implement and maintain CI/CD pipelines for automated deployment and release management of data solutions

- Administration of Snowflake warehouses, databases, schemas, and role-based security - Management of AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch - Implementation and maintenance of CI/CD pipelines for data deployments

- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field - Relevant industry certifications in AWS, Snowflake, or dbt are highly desirable Employment type

Experience Range: 8- 10 years of experience in data engineering, with hands-on expertise in Snowflake, dbt, and AWS cloud services Key Responsibilities: - Develop, maintain, and optimize dbt models, macros, and tests to support scalable ETL/ELT data pipelines - Administer and manage Snowflake data warehouses, including databases, schemas, roles, and security configurations to ensure robust data governance

- Collaborate closely with analytics, business intelligence, and engineering teams to deliver high-impact, scalable data solutions aligned with business objectives - Medallion modeling: Design, build, and maintain dbt models across Bronze → Silver → Gold layers for the assigned domain. - Governance alignment: Partner with the Data Governance team so models meet certification and quality-gate standards before promotion.

- Advanced proficiency in SQL (basic and advanced) - Expertise in developing and managing dbt models, macros, and tests - Hands-on experience with Snowflake data warehousing, including Time Travel and Fail Safe features

- Develop, maintain, and optimize dbt models, macros, and tests to support scalable ETL/ELT data pipelines - Administer and manage Snowflake data warehouses, including databases, schemas, roles, and security configurations to ensure robust data governance - Optimize complex SQL queries and warehouse performance, reducing processing times and improving storage utilization

- Expertise in developing and managing dbt models, macros, and tests - Hands-on experience with Snowflake data warehousing, including Time Travel and Fail Safe features - Strong understanding of ETL/ELT fundamentals and best practices

- Proficiency in Python for data engineering and automation tasks - Administration of Snowflake warehouses, databases, schemas, and role-based security - Management of AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch

- Knowledge of infrastructure-as-code tools for cloud resource management - Exposure to advanced Snowflake features such as data sharing and secure data exchange Desired Qualifications: