Data Engineer - Machine Learning; Marketing Analytics

Job Category: Marketing

Requisition Number: DATAE
005287

• Posted:
  November 19, 2025
• Full-Time
• On-site

Showing 1 location

Clearwater, FL 33762, USA

At PODS (Portable On Demand Storage), we’re not just a leader in the moving and storage industry, we redefined it. Since 1998, we’ve empowered customers across the U.S. and Canada with flexible, portable solutions that put customers in control of their move. Whether it’s a local transition or a cross‑country journey, our personalized service makes any experience smoother, smarter, and more human.

We’re driven by a culture of trust, authenticity, and continuous improvement. Our team is the heartbeat of our success, and together we strive to make each day better than the last. If you’re looking for a place where your work matters, your ideas are valued, and your growth is supported— PODS is your next destination.

The Data Engineer – Machine Learning is responsible for scaling a modern data & AI stack to drive revenue growth, improve customer satisfaction, and optimize resource utilization. As an ML Data Engineer, you will bridge data engineering and ML engineering: build high‑quality feature pipelines in Snowflake/Snowpark, Databricks, product ionize and operate batch/real‑time inference, and establish MLOps/LLMOps practices so models deliver measurable business impact at scale.

Note: This role is required onsite at PODS headquarters in Clearwater, FL. The onsite working schedule is Monday – Thursday onsite with Friday remote.

It is NOT a remote opportunity.

• Medical, dental, and vision insurance
• Employer‑paid life insurance and disability coverage
• 401(k) retirement plan with employer match
• Paid time off (vacation, sick leave, personal days)
• Paid holidays
• Parental leave / family leave
• Bonus eligibility / incentive pay
• Employee assistance program (EAP)
• Commuter benefits / transit subsidies (if available)
• Other fringe benefits (e.g. wellness credits)

• Design, build, and operate feature pipelines that transform curated datasets into reusable, governed feature tables in Snowflake
• Productionize ML models (batch and real‑time) with reliable inference jobs/APIs, SLAs, and observability
• Setup processes in Databricks and Snowflake/Snowpark to schedule, monitor, and auto‑heal training/inference pipelines
• Collaborate with our Enterprise Data & Analytics (ED&A) team centered on replicating operational data into Snowflake, enriching it into governed, reusable models/feature tables, and enabling advanced analytics & ML—with Databricks as a core collaboration environment
• Partner with Data Science to optimize models that grow customer base and revenue, improve CX, and optimize resources
• Implement MLOps/LLMOps: experiment tracking, reproducible training, model/asset registry, safe rollout, and automated retraining triggers
• Enforce data governance & security policies and contribute metadata, lineage, and definitions to the ED&A catalog
• Optimize cost/performance across Snowflake/Snowpark and Databricks
• Follow robust and established version control and Dev Ops practices
• Create clear runbooks and documentation, and share best practices with analytics, data engineering, and product partners

DELIVER QUALITY RESULTS:
Able to deliver top quality service to all customers (internal and external);
Able to ensure all details are covered and adhere to company policies;
Able to strive to do things right the first time;
Able to meet agreed‑upon commitments or advises customer when deadlines are jeopardized;
Able to define high standards for quality and evaluate products, services, and own performance against those standards

TAKE INITIATIVE:
Able to exhibit tendencies to be self‑starting and not wait for signals;
Able to be proactive and demonstrate readiness and ability to initiate action;
Able to take action beyond what is required and volunteers to take on new assignments;
Able to complete assignments independently without constant supervision

BE INNOVATIVE / CREATIVE:
Able to examine the status quo and consistently look for better ways of doing things;
Able to recommend changes based on analyzed needs;
Able to…