Sr. Data Engineer- Analytics

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

Job Description

Insight Global is seeking an experienced Senior Analytics Data Engineer to design, build, and maintain the trusted data models and pipelines that power marketing analytics and business decision-making.

This role sits at the intersection of data engineering, analytics engineering, and marketing analytics. The ideal candidate has deep, hands‑on expertise with dbt and Snowflake, extensive experience designing dimensional data models, and a strong understanding of marketing data and measurement.

You will partner closely with Marketing stakeholders and peers on Data Engineering team to transform complex source data into reliable, scalable, and well‑documented analytical data products.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [e-mail] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Analytics, or a related discipline, or equivalent practical experience.


• 5+ years of experience in data engineering, analytics engineering, business intelligence engineering, or a related field.


• Extensive hands‑on experience developing and maintaining production dbt projects.


• Extensive hands‑on experience using Snowflake as an enterprise cloud data warehouse.


• Advanced SQL skills, including experience developing and optimizing complex transformations across large datasets.


• Strong experience with dimensional data modeling, including fact and dimension design, star schemas, slowly changing dimensions, grain definition, surrogate keys, and conformed dimensions.


• Demonstrated experience working with marketing, customer, sales, or digital‑engagement data.


• Experience building reliable ELT pipelines and transforming data from multiple operational systems.


• Strong knowledge of data warehousing, data integration, data quality, metadata, and data‑governance principles.


• Experience implementing dbt tests, documentation, macros, snapshots, incremental strategies, and reusable modeling patterns.


• Proficiency with Git-based development, pull requests, code reviews, and CI/CD practices.


• Ability to understand business requirements and translate them into maintainable technical designs.