DBT Analytics Engineer: Snowflake & Kimball Expert

InApp; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

InApp is seeking a DBT Analytics Engineer with extensive experience in data modeling, dbt, and Snowflake to transform complex legacy data into reliable, business-friendly analytical models.

The role focuses on designing Kimball-based dimensional models, building scalable dbt pipelines, implementing data quality tests and lineage, and collaborating with reporting analysts to translate requirements into robust data solutions.

Qualifications

• 57 years in data warehousing, analytics engineering, or data modeling.
• Strong expertise in Kimball methodology, star and snowflake schemas, fact and dimension tables, and SCD Types 1 and 2.
• Hands-on experience with dbt Core and/or dbt Cloud, including models, tests, incremental models, documentation, and Jinja.
• Active dbt Analytics Engineering Certification from dbt Labs is mandatory.
• Strong Snowflake experience, advanced SQL, query optimization, and performance tuning.
• Experience handling complex business logic, unnormalized datasets, and cross-system data integration.
• Strong technical communication and problem-solving skills.

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.

Skills

Data warehousing

Kimball modeling

dbt

dbt Analytics Engineering

Snowflake

SQL

Legacy data handling

Technical communication

Tools

dbt Core

dbt Cloud

Job description

InApp is seeking a DBT Analytics Engineer with extensive experience in data modeling, dbt, and Snowflake to transform complex legacy data into reliable, business-friendly analytical models.

The role focuses on designing Kimball-based dimensional models, building scalable dbt pipelines, implementing data quality tests and lineage, and collaborating with reporting analysts to translate requirements into robust data solutions.