Senior Support Engineer I
New
A
AfreshGrocery AI
Location: Remote - United StatesFull-TimeSenior
Salary$130k to $195k + meaningful early stage equity
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Job Details
- Experience
- 5+ years in technical support engineering, solutions engineering, data engineering, or a comparable role where you personally owned root-cause analysis on production data
- Required Skills
- PythonSQLDatabricksLooker
Requirements
- Have 5+ years in technical support engineering, solutions engineering, data engineering, or a comparable role owning root-cause analysis on production data.
- Demonstrate advanced SQL skills, including reasoning across large, imperfect datasets and validating findings against authoritative sources.
- Own complex cross-functional initiatives end to end and secure commitments from other teams.
- Define numerical measures of success before starting work and report results.
- Build with AI tools such as Claude or other agentic platforms and exercise judgment about appropriate automation.
- Use Python or similar scripting to automate investigation and data work.
- Communicate clearly and calmly in writing and teach less experienced teammates.
- Work independently, set milestones, and make progress amid ambiguity.
- Grocery, retail, or supply chain knowledge is an advantage; familiarity with ordering, replenishment, assortment, or fresh department operations is beneficial.
- Experience with Databricks, Zendesk, Stylo, or workflow automation platforms is a plus.
- Experience supporting ML-driven products and distinguishing data-input, model, and application-logic anomalies is a plus.
- A track record of mentoring engineers and raising a team's technical bar is a plus.
Responsibilities
- Own complex escalations involving data mapping defects, recommendation and forecast anomalies, and integration or data-feed failures.
- Lead initiatives that improve ticket deflection, average handle time, and escalations to cross-functional teams.
- Define success metrics, measure impact, and publish regular results to relevant teams and leaders.
- Build tooling and automations using SQL, Python, Databricks, Looker, Stylo, Claude, and Cowork.
- Partner with Solutions Engineering, Data Engineering, Product Engineering, and Operations to address root causes.
- Mentor Tier 1 and Tier 2 engineers, lead training, and write playbooks and source-of-truth documentation.
- Present in Tech Demos, share data-driven updates, participate in account reviews, and represent Support in cross-functional forums.
- Develop expertise in retailer- and banner-specific behavior and serve as an escalation point for decisions involving Product, Engineering, or customers.
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