Senior DBT and Snowflake Data Engineer

As a DBT/Snowflake Engineer, you will play a crucial role in a large-scale Data Modernization Program. Your responsibilities will include: - Translating Informatica mappings, transformations, and business rules into dbt models (SQL) on Snowflake. - Designing and implementing staging, core, and mart layers using standard dbt patterns and folder structures. - Developing and maintaining dbt tests (schema tests, data tests, custom tests) to ensure data quality and integrity. - Implementing snapshots, seeds, macros, and reusable components where appropriate. - Collaborating with Snowflake developers to ensure physical data structures support dbt models efficiently. - Working with functional teams to ensure functional equivalence between legacy Informatica outputs and new dbt outputs. - Participating in performance tuning of dbt models and Snowflake queries. - Integrating dbt with CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for automated runs and validations. - Contributing to documentation of dbt models, data lineage, and business rules. - Participating in defect analysis, bug fixes, and enhancements during migration and stabilization phases. Qualifications required for this role include: - 7+ years of experience in Data Engineering/ETL/DW, with 13+ years working with dbt (Core or Cloud). - Strong SQL skills, especially on Snowflake or another modern cloud DW. - Experience with dbt concepts: models, tests, sources, seeds, snapshots, macros, exposures. - Prior experience with Informatica (developer-level understanding of mappings/workflows) is highly desirable. - Understanding of CI/CD practices and integrating dbt into automated pipelines. - Knowledge of data modeling (dimensional models, SCDs, fact/dimension design). - Experience working in offshore delivery with onshore coordination. - Good communication skills and ability to read/understand existing ETL logic and requirements documentation. This position is at the Senior Level, and your expertise will be invaluable in driving the success of the Data Modernization Program. As a DBT/Snowflake Engineer, you will play a crucial role in a large-scale Data Modernization Program. Your responsibilities will include: - Translating Informatica mappings, transformations, and business rules into dbt models (SQL) on Snowflake. - Designing and implementing staging, core, and mart layers using standard dbt patterns and folder structures. - Developing and maintaining dbt tests (schema tests, data tests, custom tests) to ensure data quality and integrity. - Implementing snapshots, seeds, macros, and reusable components where appropriate. - Collaborating with Snowflake developers to ensure physical data structures support dbt models efficiently. - Working with functional teams to ensure functional equivalence between legacy Informatica outputs and new dbt outputs. - Participating in performance tuning of dbt models and Snowflake queries. - Integrating dbt with CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for automated runs and validations. - Contributing to documentation of dbt models, data lineage, and business rules. - Participating in defect analysis, bug fixes, and enhancements during migration and stabilization phases. Qualifications required for this role include: - 7+ years of experience in Data Engineering/ETL/DW, with 13+ years working with dbt (Core or Cloud). - Strong SQL skills, especially on Snowflake or another modern cloud DW. - Experience with dbt concepts: models, tests, sources, seeds, snapshots, macros, exposures. - Prior experience with Informatica (developer-level understanding of mappings/workflows) is highly desirable. - Understanding of CI/CD practices and integrating dbt into automated pipelines. - Knowledge of data modeling (dimensional models, SCDs, fact/dimension design). - Experience working in offshore delivery with onshore coordination. - Good communication skills and ability to read/understand existing ETL logic and requirements documentation. This position is at the Senior Level, and your expertise will be invaluable in driving the success of the Data Modernization Program.