Senior Analytics Data Engineer - Marketing Data & dbt

Insight Global; Arden Hills (MN); On-site; USD 120,000 - 160,000; Full time

Job summary

Insight Global is seeking a Senior Analytics Data Engineer to design, build, and maintain trusted data models and pipelines powering marketing analytics and business decision‑making.

This role sits at the intersection of data engineering, analytics engineering, and marketing analytics, requiring deep dbt and Snowflake expertise and strong dimensional modeling skills to transform complex source data into reliable analytical data products for stakeholders.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5+ years in data engineering, analytics engineering, BI engineering, or related field.
• Extensive hands-on dbt production projects.
• Extensive Snowflake enterprise data warehouse experience.
• Advanced SQL with transformations across large datasets.
• Strong dimensional modeling: star schemas, SCDs, surrogate keys.
• Experience with marketing, customer, sales, or digital‑engagement data.
• Experience building reliable ELT pipelines from multiple systems.
• Knowledge of data warehousing, data integration, quality, metadata and governance.
• dbt tests, documentation, macros, snapshots, incremental strategies.
• Git-based development and CI/CD practices.
• Translate business requirements into maintainable technical designs.

Responsibilities

• Design, build, and maintain data models and pipelines for marketing analytics.
• Partner with Marketing and Data Engineering to deliver analytic data products.
• Document data products and ensure data quality and governance.

Skills

SQL

ELT pipelines

Marketing data

Git workflows

CI/CD practices

Dimensional data modeling

Education

Bachelor’s degree in CS/IS/Engineering/Data Analytics or equivalent

Tools

dbt

Snowflake

Job description

Insight Global is seeking a Senior Analytics Data Engineer to design, build, and maintain trusted data models and pipelines powering marketing analytics and business decision‑making.

This role sits at the intersection of data engineering, analytics engineering, and marketing analytics, requiring deep dbt and Snowflake expertise and strong dimensional modeling skills to transform complex source data into reliable analytical data products for stakeholders.