Shake Shack
hospitality
AnalyticsEngineer–DataQualityLead
Neural analysis suggests this role is
optimal for Mid candidates.
“Analytics Engineer – Data Quality Lead at Shake Shack. Skills: dbt, SQL, Data Quality, Analytics Engineering, Data Modeling, AI tooling. Design, develop, and maintain dbt models, SQL transformations, and data pipelines. Build and optimize dimensional data models”
What You'll Achieve.
Ensure that what gets built is not only functional but reliable, documented, and trustworthy; Accelerating both personal output and broader team capability using AI tooling; Raising overall delivery quality across the ecosystem; Reduce cost and improve end-user experience; Promote transparency and enable knowledge sharing; Detect anomalies, freshness failures, and quality regressions before they surface in dashboards or downstream systems; Reduce silent failures and undocumented assumptions
Industry & Context.
Analytical thinking; Attention to detail; Ability to identify and resolve data quality issues
What They're Looking For.
Must Have
3+ years of experience in analytics engineering, data modeling, or a closely related data delivery role focused on transforming raw data into analytics-ready datasets, proficiency in SQL, hands-on experience with dbt, including testing frameworks, documentation standards, and model governance, Experience working with cloud data warehouses (Snowflake, BigQuery, Redshift, or similar), Demonstrated understanding of data modeling concepts including dimensional modeling, star/snowflake schemas, and normalization, Experience working in a delivery model that includes offshore, vendor, or service partner resources, with direct accountability for reviewing and accepting their technical output, Familiarity with data quality monitoring concepts including row count validation, freshness checks, null rate monitoring, and referential integrity testing, Active, daily use of AI coding assistants (GitHub Copilot, Cursor, Claude, or similar) as a core part of engineering workflow rather than occasional experimentation, Familiarity with version control (Git) and software engineering best practices including branching, code review, and CI/CD concepts, analytical thinking and attention to detail, with a demonstrated ability to identify and resolve data quality issues before they reach end users, Effective communication and stakeholder management skills, with the ability to give direct technical feedback to partners and translate data concepts for non-technical audiences
Nice to Have
Hands-on experience with data observability platforms such as Elementary, re_data, Monte Carlo, or Soda Core, Experience defining or enforcing data contracts or SLA-style quality agreements between data producers and consumers, Experience with CI/CD pipeline concepts applied to dbt projects, including automated testing gates and deployment workflows, Knowledge of Python for data transformation, automation, or pipeline scripting, Experience with data orchestration tools such as Airflow, Dagster, or Prefect, Familiarity with business intelligence and data visualization tools (Tableau, Looker, Power BI, or similar), with an understanding of how upstream model decisions affect downstream reporting, Understanding of machine learning workflows and feature engineering requirements, including how to structure data models for ML model training and validation, Experience in retail, hospitality, QSR, or restaurant operations environments, Exposure to event tracking, product analytics, or marketing analytics data domains, Experience collaborating with Data Science teams on analytical or ML projects, translating modeling requirements into data product specifications, 5+ years of total experience in analytics engineering, data analysis, or a related field
What You'll Do.
and maintain dbt models
Build and optimize dimensional data models
Own high-complexity internal workstreams such as semantic layer definitions
cross-domain data models
and metrics standardization
Support query performance optimization and data warehouse efficiency
Develop and maintain clear documentation of data models
Serve as the internal technical quality gate for service partner deliverables
Use AI-assisted code review tooling
Own and continuously improve the team's data observability posture
Build and enforce pre-deployment checklists and release gate criteria
Define and maintain data contracts between data producers and consumers
Provide technical guidance and mentorship to service partner resources and extended team members
How You'll Work.
Team & Collaboration
Partner with the Business Analyst, Data Product Lead, and Product Manager to translate business requirements into scalable, well-scoped data solutions; Collaborate with Data Engineering to ensure reliable upstream pipelines; Collaborate with analytics consumers across Operations, Finance, Marketing, and other business units to understand data needs and validate delivered solutions; Act as a trusted technical voice in program and project delivery conversations
Communication Scope
Effective communication and stakeholder management skills; Ability to give direct technical feedback to partners; Ability to translate data concepts for non-technical audiences
Full Job Description
**Our secret to leading the way in hospitality? We put our people first!** At Shake Shack, our mission is to Stand For Something Good in all that we do. From our teams to our neighborhoods, we're committed to always doing the right thing. As one of the fastest-growing hospitality brands, we're all about crafting unforgettable experiences for our guests. We offer endless learning opportunities and the chance to make a lasting impact on our business, restaurants, and communities. As a member of the #ShackFam, you’ll have access to hands-on mentorship, training, and growth potential, all in a fun and inclusive environment. Join us and Be a Part of Something Good. **Job Summary** We are seeking an Analytics Engineer with a quality-first mindset to join our Data & Analytics team. This role is responsible for designing, building, and maintaining robust data models, pipelines, and analytics infrastructure across a broad, multi-domain portfolio, while simultaneously serving as the internal technical quality gate for a delivery model that includes our internal team and external service partners. The Analytics Engineer: Data Quality Lead bridges hands-on engineering with oversight and standards-setting, ensuring that what gets built is not only functional but reliable, documented, and trustworthy. This role operates within a modern data stack environment and is expected to leverage AI tooling as a core part of day-to-day workflow, accelerating both personal output and broader team capability. The ideal candidate has 3+ years of analytics engineering experience with strong dbt and SQL proficiency, a track record of working in vendor or offshore delivery models, and the technical judgment to review others' code with precision and confidence. They understand that data quality is not a phase at the end of a project but a discipline embedded in every model, every test, and every deployment decision. They get energy from making systems more reliable, not just shipping their own wor
Applying for this Analytics Engineer – Data Quality Lead role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about Shake Shack?
Real rants from real employees. Read before you apply.