Senior Data Engineer - Snowflake & dbt Pipelines

Kapitus, Inc.; Arlington (VA); Remote; USD 96,000 - 154,000; Full time

Benefits offered by this job

Health Insurance

401K with 25% match

Paid Time Off

Tuition Reimbursement

Flexible Spending Account

Job summary

Kapitus is looking for a Senior Data Engineer to design and deliver scalable data pipelines on Snowflake and dbt. You will model data within a medallion architecture, enforce data contracts, and migrate legacy analytics workloads to the modern stack.

You will also implement data quality and observability as code across the platform. The role emphasizes collaboration across distributed teams, governance-focused modeling, and cost-conscious engineering practices, with opportunities for leadership

Qualifications

• 5+ years hands-on data engineering building production pipelines and warehouse models.
• Senior-level candidates (8+ years) with workstream leadership and design ownership.

Responsibilities

• Develop ELT pipelines on Snowflake and dbt for ingestion, transformations, and serving structures.
• Model data across staging, conformed core entities, and dimensional models per standards.
• Migrate legacy analytics workflows (e.g., Alteryx) to Snowflake/dbt with parity Testing.
• Implement data quality as code with dbt tests and source freshness checks.
• Build reusable ingestion frameworks and common transformation patterns.
• Work with Git, CI/CD, and documentation to support operability.
• Profile query performance and manage Snowflake compute costs.
• Provide production support with observability and incident analysis.

Skills

Snowflake

dbt

SQL

Python

Data modeling

Git

CI/CD

Data quality

Tools

Alteryx

SSIS

SAS

Tableau

Dagster

dbt certification

Job description

Kapitus is looking for a Senior Data Engineer to design and deliver scalable data pipelines on Snowflake and dbt. You will model data within a medallion architecture, enforce data contracts, and migrate legacy analytics workloads to the modern stack.

You will also implement data quality and observability as code across the platform. The role emphasizes collaboration across distributed teams, governance-focused modeling, and cost-conscious engineering practices, with opportunities for leadership