dbt Data Engineer / Developer (Snowflake)

Role Overview: We are looking for a hands-on dbt Data Engineer / Developer to build, test, and maintain scalable ELT transformation pipelines using dbt, SQL, Snowflake, and modern cloud data platforms. · Design, develop, and maintain dbt models for staging, intermediate, and mart layers.

· Design, develop, and maintain dbt models for staging, intermediate, and mart layers. · Build ELT pipelines using SQL, dbt, and Snowflake, including staging, transformation, and data mart layers; exposure to Databricks, BigQuery, Redshift, or Azure Synapse is an added advantage. · Implement dbt tests, documentation, source freshness checks, snapshots, and reusable macros.

· Implement dbt tests, documentation, source freshness checks, snapshots, and reusable macros. · Optimize SQL queries and dbt models for performance, reliability, and maintainability. · Work with analysts, business users, and senior data engineers to translate requirements into data models and transformation logic.

· Support Git-based development, pull requests, code reviews, CI/CD deployments, and environment management. · Exposure to legacy data warehouse migration or modernization initiatives, preferably involving Teradata to Snowflake migration, including support for SQL conversion, data validation, reconciliation, and defect fixes. · Troubleshoot pipeline failures, data quality issues, and production defects in collaboration with platform and support teams.

· Strong hands-on experience with dbt Core or dbt Cloud. · Advanced SQL skills with experience in complex transformations and performance tuning. · Good understanding of dimensional modelling, star schema, data marts, and warehouse concepts.

· Good understanding of dimensional modelling, star schema, data marts, and warehouse concepts. · Hands-on experience with Snowflake, including SQL development, warehouse usage, schemas, tables, views, access roles, and performance-aware query design. · Good understanding of Snowflake objects such as databases, schemas, virtual warehouses, stages, file formats, streams, tasks, and secure views.

· Good understanding of Snowflake objects such as databases, schemas, virtual warehouses, stages, file formats, streams, tasks, and secure views. · Good understanding or hands-on exposure to Teradata concepts, SQL, data warehouse objects, BTEQ scripts, stored procedures, views, and migration activities from Teradata to Snowflake. · Experience supporting migration testing, source-to-target validation, record count checks, data quality checks, and comparison of migrated data between Teradata and Snowflake.

We are looking for a hands-on dbt Data Engineer / Developer to build, test, and maintain scalable ELT transformation pipelines using dbt, SQL, Snowflake, and modern cloud data platforms. · Design, develop, and maintain dbt models for staging, intermediate, and mart layers. · Build ELT pipelines using SQL, dbt, and Snowflake, including staging, transformation, and data mart layers; exposure to Databricks, BigQuery, Redshift, or Azure Synapse is an added advantage.

· Build ELT pipelines using SQL, dbt, and Snowflake, including staging, transformation, and data mart layers; exposure to Databricks, BigQuery, Redshift, or Azure Synapse is an added advantage. · Implement dbt tests, documentation, source freshness checks, snapshots, and reusable macros. · Optimize SQL queries and dbt models for performance, reliability, and maintainability.

· Strong experience in data engineering, ETL/ELT development, analytics engineering, or data warehousing. · Strong hands-on experience with dbt Core or dbt Cloud. · Advanced SQL skills with experience in complex transformations and performance tuning.

· Hands-on experience with Snowflake, including SQL development, warehouse usage, schemas, tables, views, access roles, and performance-aware query design. · Good understanding of Snowflake objects such as databases, schemas, virtual warehouses, stages, file formats, streams, tasks, and secure views. · Good understanding or hands-on exposure to Teradata concepts, SQL, data warehouse objects, BTEQ scripts, stored procedures, views, and migration activities from Teradata to Snowflake.

· Good understanding or hands-on exposure to Teradata concepts, SQL, data warehouse objects, BTEQ scripts, stored procedures, views, and migration activities from Teradata to Snowflake. · Experience supporting migration testing, source-to-target validation, record count checks, data quality checks, and comparison of migrated data between Teradata and Snowflake. · Good-to-have exposure to mainframe data sources, including COBOL copybooks, VSAM files, DB2 on z/OS, JCL, batch files, flat files, and mainframe-to-cloud data extraction patterns.