Invent L3 Engineer – Retail Planning Support Specialist (Invent.ai / MerchPlan)

Experience: 6–10 Years

Budget: 1.1L-1.8L

JD:

• Reproduce issues in test environments and prepare detailed defect documentation including:
o Logs
o SQL extracts
o Reproduction steps
o Technical findings for Engineering teams
• Coordinate and implement:
o Permanent fixes
o Product patches
o Configuration updates
o R&D and Product team resolutions
• Lead technical readiness activities for:
o Go-lives
o Product upgrades
o Capacity testing
o Pre/Post reconciliation
o Cutover support
o Runbook management
• Perform performance tuning for:
o Forecast execution jobs
o SQL/database queries
o Runtime optimization
o Scaling and partitioning recommendations
• Create and maintain:
o Runbooks
o Knowledge Base (KB) articles
o Troubleshooting documentation
• Participate in on-call support rotation for production environments.

Required Skills & Qualifications
• 6+ years of experience in:
o Merchandise planning systems
o Forecasting platforms
o Retail planning support/implementation
• Mandatory experience with:
o Invent.ai / MerchPlan
• Strong retail domain knowledge in:
o Forecasting
o OTB (Open-to-Buy)
o Assortment Planning
o Allocation
o Replenishment
o Promotions
o Markdown Optimization
o Seasonality Planning
• Strong SQL expertise including:
o Complex queries
o Window functions
o Performance tuning
o Data validation and reconciliation
• Hands-on experience with:
o SFTP
o CSV/Flat files
o REST APIs
o ETL troubleshooting
• Scripting knowledge in:
o Python
o Bash
• Good understanding of:
o Linux environments
o Log analysis
o Multi-tenant SaaS platforms
• Proven experience handling:
o High severity production incidents
o RCA documentation
o Business-impact communication
• Excellent verbal and written communication skills with the ability to explain technical issues to business stakeholders.

Preferred Candidate Profile
• Strong analytical and troubleshooting mindset
• Experience working with retail merchandising and finance teams
• Ability to work in fast-paced production support environments