Resolution Manager Jobs in Omaha, NE (NOW HIRING)

About Milan Laser Hair Removal

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 we continue to grow, so does the importance of the technology and data behind our business. We’re looking for a Data Platform Manager who can lead the evolution of Milan’s data platform while staying close to the technical work that makes it all happen.

Position Summary

Lead a team responsible for the architecture, roadmap, and delivery of Milan’s Snowflake data platform, including ingestion, the data lakehouse, identity resolution, and data engineering of foundational datasets so the organization has a reliable, scalable data foundation for today’s analytics and reporting and tomorrow’s artificial intelligence (AI) initiatives. Remain a hands-on technical contributor to the team’s most complex data engineering and architectural work rather than a resource manager alone. Drive technical standards and patterns that guide day-to-day data architecture decisions across the team. Partner with cross-functional leaders to translate business priorities into platform capabilities. Build the technical and professional capabilities of the team through coaching, feedback, and performance management.

Status: Full-time | Salaried
Location: Omaha, NE | On-Site

Responsibilities

• Platform Architecture & Technical Strategy: Inform the technical architecture and drive the roadmap for Milan’s Snowflake data platform, including ingestion, the medallion architecture lakehouse, identity resolution, and data engineering of foundational datasets. Make and document architectural decisions that balance near-term delivery with long-term reusability, scalability, and maintainability. Evaluate new tools, patterns, and approaches (e.g., managed ingestion, governed transformation frameworks, data observability) and recommend where Milan should build versus buy.
• Team Leadership & People Management: Hire, coach, and manage the performance of data engineers and other technical staff on the platform team. Foster a culture of technical craftsmanship, accountability, and continuous improvement. Set clear goals and provide regular feedback to support each team member’s growth and development.
• Delivery & Prioritization: Prioritize and manage delivery of platform initiatives, including ingestion, identity and journey stitching, customer 360, data quality, and medallion layers that enable business intelligence, data science, and AI/agentic workloads. Break down complex technical roadmaps into achievable milestones and manage progress against them. Escalate risks, trade-offs, and resourcing needs to leadership early and clearly.
• Hands-On Engineering: Contribute directly to the design and development of complex data pipelines, data models, and platform components alongside the team. Perform code reviews and drive the use of reusable standards, templates, and best practices in conjunction with Principal Data Architect. Collaborate with the team to troubleshoot and resolve technical issues that arise.
• Cross-Functional Partnership: Partner with the Business Intelligence Manager and other data and business leaders to align platform capabilities with reporting, analytics, and activation needs. Represent the data platform in conversations with cross-functional departments and external partners. Communicate technical direction, progress, and constraints clearly to both technical and non-technical audiences.

Qualifications

• 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
• Six 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
• Demonstrated experience designing and implementing lakehouse or medallion (Bronze/Silver/Gold) data architecture required
• Three years of Python or other scripting language experience required
• Two years of experience directly managing, leading, or mentoring data engineers or similar technical staff 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 technical direction and trade-offs to both business and technical audiences required
• Effective written and verbal communication skills required
• Snowflake or Databricks experience required
• Experience evaluating build-versus-buy decisions for data tooling and infrastructure preferred
• Salesforce API and data pipeline experience preferred
• Experience working in an Agile/Scrum project development environment preferred

Benefits

• Medical, dental, vision, disability and life insurance within 30 days
• Paid time off starting immediately
• 6 Paid holidays
• $50 cellphone stipend paid out monthly
• 401k retirement plan with vested 4% employer match after 90 days
• Career advancement opportunities + Culture/environment
• Employees and their spouse or legal partner receive free laser hair removal services

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Other duties may be assigned.

We are deeply committed to attracting talented team members in the US from all backgrounds regardless of race, age, gender, ethnicity, religion, sexual orientation, disability status, or nationality. However, at this time, we are not sponsoring any Visas.

Equal Opportunity Employer

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