TUMI→
IT Intern
InternshipOn-site
Location
Edison, NJ
Salary
Not listed
Experience
No experience required
Posted
1 week ago
Skills
sqlpythonecommerce conceptsretail data engineeringsnowflakemachine learning basicsdbtairflowgitai/llm conceptsdocumentation mindset
Job Description
Summary: TUMI is a company known for creating world-class business and travel essentials. The IT Intern will work with various teams across the IT department to support Retail and E-commerce analytics by building pipelines, enhancing data quality, and deploying AI agents.
Responsibilities:
- Retail Data Ingestion & Pipelines by building or enhancing ingestion for common retail feeds. Implement Snowflake loading patterns with optional automation (if applicable)
- Retail Data Modeling (SQL) by creating curated analytics-ready tables from raw feeds. Support omnichannel reporting by connecting various internal and external retail data elements
- Data Quality & Reconciliation (with Agent Automation) by implementing retail-relevant checks like uniqueness/deduping of customers, referential integrity (orders, product/store IDs) and anomaly detection (drops/spikes in sales, cancellations, returns). Build an agent to automate quality check and reporting
- Participate in system and integration testing in various other initiatives running in the departments
- Build and Deploy Agents to Execute at Scale - from learning to Production
- Phase 1 — Sandbox Learning (Weeks 1–3) Build a simple agent to generate validation SQL from templates and produce a report
- Phase 2 — Controlled Pilot (Weeks 4–7) Expand to scheduled runs, consistent output, and alerting
- Phase 3 — Scale & Hardening (Weeks 8–12) Add guardrails (scope-limited actions), logging/audit trail, performance controls, and human review workflows
- Build ML Models for Forecasting & Predictions (Retail Use Cases) by working with a mentor to design and prototype a predictive model using curated datasets
- Feature set definition (lags, rolling windows, promos, seasonality)
- Testing approach (time-based splits)
- Model training and evaluation
- Forecast outputs written back into data tables for reporting
- Basic explainability summary (top drivers / feature importance)
- By the end of the internship, the person should have delivered:
- Production-ready ingestion pipelines into Snowflake (raw → staging)
- Curated retail data models (fact/dim tables)
- A data quality suite with automated checks (SQL and Python)
- At least one deployed agent that executes repeatable tasks at scale (logging and guardrails)
- One forecasting/prediction prototype with documented accuracy
- Documentation: data dictionary plus pipeline runbook plus lineage plus model card
- A final demo showing measurable improvements (quality, timeliness, usability, or forecast accuracy)
Required Qualifications:
- Candidate must be enrolled/actively pursuing a degree in an IT-based field
- High School diploma required
- Working knowledge of SQL (joins, aggregations; window functions preferred)
- Python basics (pandas, file/JSON handling, API calls)
- Strong attention to detail; ability to learn fast
- Clear communication and documentation mindset
- Great organization skills, attention to detail, and time management skills
- Excellent communication skills
- Ability to work independently and as part of a team
Preferred Qualifications:
- Exposure of ecommerce concepts (orders, promotions, returns, inventory, POS)
- Interest in retail/ecommerce data and data engineering
- Exposure to Snowflake or any cloud data warehouse
- Basic ML familiarity (time series, regression, evaluation metrics)
- Familiarity with dbt, Airflow, or orchestration tools
- Git/version control
- Interest in AI/LLM concepts, evaluation, and safe automation patterns
Required Skills: SQL, Python, Ecommerce concepts, Retail data engineering, Snowflake, Machine learning basics, dbt, Airflow, Git, AI/LLM concepts, Documentation mindset