Software Engineer, Data Engineer, Data Analyst

We believe shopping should feel like winning. That’s why 10 million people come to Slickdeals to swap tips, upvote the best finds, and share the thrill of a great deal. Together, our community has saved more than $10 billion over the past 26 years.

We’re profitable, passionate, and in the middle of an exciting evolution—transforming from the internet’s most trusted deal forum into the go-to daily shopping destination. If you thrive in a fast-moving, creative environment where ideas turn into impact fast, you’ll fit right in.

Slickdeals is seeking a Staff Software Engineer with deep expertise in Big Data platforms/systems to lead and evolve our data engineering ecosystem. This role goes beyond pipeline maintenance; it’s about architecting scalable, resilient platforms that power analytics, experimentation, and machine learning across the business. You’ll inherit a mature platform built over 3+ years, spanning Databricks, dbt, Airflow, AWS, Tableau, and AtScale, and drive its next phase of growth.

As a technical leader, you’ll shape architecture, mentor engineers, and ensure our data infrastructure supports analytics, experimentation, and business enablement at scale.

• Architect, evolve, and maintain core ETL/ELT pipelines using dbt, Airflow, and Databricks
• Design and optimize semantic models in AtScale to support BI tools like Tableau
• Lead cross-functional collaboration with Analytics, Product, and Engineering to deliver reliable, timely data
• Own observability, performance, and reliability of data workflows across environments
• Guide infrastructure decisions in AWS (S3, Kafka, EC2, Lambda, IAM), balancing scalability and cost
• Drive cost optimization and platform hygiene across data storage, compute, and tooling
• Champion CI/CD practices and automated testing for data pipelines and infrastructure-as-code
• Uphold engineering rigor through SDLC best practices, including version control, peer reviews, and reproducible builds
• Lead documentation efforts, promote reproducibility, and support onboarding for long-term team health
• Facilitate code reviews, lead architecture discussions, champion engineering excellence, and contribute to overall technical strategy
• Mentor engineers and foster a culture of knowledge sharing and continuous learning

• BS/BA/BE degree in a quantitative area such as mathematics, statistics, economics, computer science, engineering, or equivalent experience.
• 12+ years of experience in software engineering
• 7+ years of experience in building large scale data solutions
• Strong proficiency in SQL, Python, and dbt
• Hands‑on experience with Databricks, Airflow, and AWS infrastructure
• Strong understanding of semantic modeling
• Experience building dashboards and supporting BI teams using Tableau
• Familiarity with CI/CD pipelines, automated testing, and infrastructure-as-code workflows
• Experience with data governance, security, and compliance best practices
• Deep understanding of SDLC principles and how they apply to data engineering
• Excellent communication and documentation skills
• Comfortable working in a fast-paced, collaborative environment
• Strategic mindset with a bias for action, always curious and a continuous learner

• Experience with cost monitoring tools or Fin Ops practices
• Experience with Machine Learning and Data Science
• Familiarity with vendor integrations and API-based data sharing
• Exposure to AtScale, Tableau, or other modern data platforms
• Passion for mentoring and knowledge sharing

With your application, kindly attach a cover letter that outlines your greatest achievement. Please share what you built, how you measured success, and your role in the result.

Please note:

We are unable to sponsor visas at this time. Candidates must be authorized to work in the U.S. without current or future visa sponsorship or transfer.

LOCATION:
Las Vegas, NV

Hybrid schedule visiting our Las Vegas office three days a week (Tues-Thurs).

The expected base pay for this role is between $186,000 - $212,000. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Exact compensation will be discussed during…