Jobs → Engineering → DBT Analytics Engineer

About the Role We are looking for a DBT Analytics Engineer with 7–12 years of experience in data modeling, dbt, and Snowflake. The candidate will be responsible for transforming complex legacy data into reliable analytical models. Key Responsibilities • Design and develop dimensional data models using Kimball methodology. • Build and maintain scalable dbt models in Snowflake. • Transform complex, unnormalized legacy data into a reliable single source of truth. • Implement data quality tests, documentation, and data lineage. • Optimize SQL queries and analytical models for performance. • Collaborate with reporting analysts and stakeholders to translate business requirements into data models. • Communicate modeling decisions, code changes, and downstream impacts clearly. Requirements • Experience: 5–7 years in data warehousing, analytics engineering, or data modeling. • Data Modeling: Strong expertise in Kimball methodology, star and snowflake schemas, fact and dimension tables, and SCD Types 1 and 2. • dbt: Hands-on experience with dbt Core and/or dbt Cloud, including models, tests, incremental models, documentation, and Jinja. • Certification: Active dbt Analytics Engineering Certification from dbt Labs is mandatory. • Snowflake & SQL: Strong Snowflake experience, advanced SQL, query optimization, and performance tuning. • Legacy Data: Experience handling complex business logic, unnormalized datasets, and cross-system data integration. • Communication: Strong technical communication and problem-solving skills. Preferred Skills • Experience with ERP, financial, accounting, payroll, or HCM data. • Familiarity with SAP, Oracle, Deltek, or CMiC.