DBT Analytics Engineer

JOB SUMMARY

We are looking for a DBT Analytics Engineer with 57 years of relevant experience in data modeling, dbt, and Snowflake. The candidate should have strong expertise in Kimball dimensional modeling and experience transforming complex legacy data into reliable, business-friendly 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.

REQUIRED SKILLS

• Experience: 57 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.