Sr. Data Engineer

At Milan Laser Hair Removal, we’re not just transforming skin—we’re transforming confidence. As the nation’s largest laser hair removal provider, we’re built on a culture of excellence, innovation, and a commitment to delivering a world-class experience for both our clients and our team.

As Milan continues to grow, so does the scale and sophistication of the data behind our business. We’re looking for a Senior Data Engineer who can help build the data foundation powering everything from business intelligence and self-service analytics to emerging artificial intelligence (AI) initiatives.

Design, build, optimize, and test the data pipelines and lakehouse architecture that power Milan’s data platform, business intelligence, and artificial intelligence (AI) initiatives. Lead the development of all layers of a Snowflake-based medallion data architecture including curated and semantic layer models that support both dashboards and advanced analytics. Solve complex data acquisition, modeling, and integration challenges across Milan’s Snowflake platform incorporating holistic Customer 360 and business data. Collaborate with other engineers on the team and raise the bar for data pipeline quality, reliability, and craftsmanship.

This is a fully on-site position within Omaha, NE.

• →Data Pipeline & Lakehouse Development: Design and build scalable ETL/ELT pipelines that integrate data from Salesforce, marketing platforms, and other disparate source systems into Milan’s Snowflake Lakehouse leveraging python, SQL, and Snowflake native functionality including Dynamic Tables. Translate business requirements into technical data models and pipeline architecture. Build data shares and integrations for external partners and downstream systems.
• →Data Modeling & Analytics Engineering: Model data across the Bronze, Silver, and Gold layers to support reporting, self-service analytics, and semantic layer consumption. Design and maintain Gold-layer datasets and semantic models that power Power BI, ad hoc analysis, and emerging AI and agentic use cases. Perform data profiling on source systems and model data for reliable downstream use.
• →Data Quality & Governance: Design and implement data quality checks, including Snowflake Data Metric Functions, to catch issues before they reach downstream users. Establish and maintain procedures that ensure data accuracy, consistency, and accessibility across the platform. Maintain code repositories using Git and enforce version control best practices.
• →Technical Leadership & Problem Solving: Lead solution design for complex data pipeline, modeling, and integration challenges. Perform code reviews and mentor other data engineers on technical craft and best practices. Troubleshoot and resolve complex data issues independently and collaboratively.
• →Documentation & Communication: Build and maintain documentation for data pipelines, data models, and architectural decisions. Communicate technical designs, trade-offs, and solutions clearly to both the data team and business stakeholders.

• High school diploma or equivalent (e.g., GED) required
• Bachelor’s degree in information technology, computer science, or a related field OR equivalent combination of education and experience combined (one year of experience equals one year of education) required
• Four years of experience building ETL/ELT systems and data pipelines in a data warehouse or lakehouse environment required
• Five years of Structured Query Language (SQL) experience required
• Three years of Python or other scripting language experience required
• Demonstrated experience building semantic layer or analytics-engineering-style data models (e.g., dbt, Power BI datasets, or equivalent) required
• Understanding of how to leverage data platforms to efficiently and cost-effectively collect, store, and use data required
• Collaborative, team-first mentality with the ability to effectively communicate with both business and technical users and team members required
• Effective written and verbal communication skills required
• Snowflake experience preferred
• Matillion or other cloud ETL platform experience preferred
• Salesforce API and data pipeline experience preferred
• Experience mentoring or reviewing the work of other engineers preferred
• Experience working in an Agile/Scrum project development environment preferred