Senior Analytical Engineer

Inapp; United States; Hybrid; USD 140,000 - 210,000; Full time

Job summary

InApp Inc. is seeking a DBT Analytics Lead Engineer with 8–12 years of experience in data modeling, dbt, and Snowflake. The role focuses on transforming complex legacy data into reliable analytical models and building scalable dbt models in Snowflake.

You will collaborate with analysts and stakeholders to translate business requirements into data models, implement data quality tests, and optimize performance. Remote/hybrid arrangement with strong communication to ensure data integrity.

Qualifications

• 8–12 years in data warehousing, analytics engineering, or data modeling.
• Active dbt Analytics Engineering Certification mandatory.
• Strong Kimball dimensional modeling expertise required.

Responsibilities

• Build and maintain scalable dbt models in Snowflake.
• Transform 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 requirements.
• Communicate modeling decisions and downstream impacts clearly.

Skills

8–12 years experience

dbt Core

dbt Cloud

Snowflake

SQL

Kimball modeling

Star/Snowflake schemas

SCD Types 1 & 2

Data modeling

Data quality tests

Data lineage

Legacy data transformation

Certification: dbt Analytics Eng

Communication skills

Tools

dbt Core

dbt Cloud

Snowflake

Job description

Experience : 8-12 Years

Project Location(s) : Remote/Hybrid

Notice Period-Immediate

Job Summary

We are looking for a DBT Analytics Lead Engineer with 8–12 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

• 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: 8–12 years in data warehousing, analytics engineering, or data modeling.
• Data Modeling: Strong expertise in Kimball methodology(Optional), 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.