> Markdown version of [/jobs/ext/2718014-spark-team-engineer](https://www.wearedevelopers.com/jobs/ext/2718014-spark-team-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Spark Team Engineer - **Company:** Nephropathology Associates, PLC - **Location:** United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Information Engineering, PostgreSQL, Node.Js, Standard Sql, Apache Spark, Data Layers - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/spark-team-engineer-arkana-laboratories-8786548 ## About the Role * Experience spanning data engineering and full-stack software work; the balance should lean data (pipelines, modeling, integration across messy source systems) with production application work behind it * Demonstrated judgment with prototypes: ones you took to production, and ones you killed along the way; expect to walk through both * Experience in regulated environments, or the judgment to operate in one from day one Required Technical Skills: * Strong SQL and PostgreSQL * Comfortable in Node.js and modern web stacks; able to pick up unfamiliar codebases quickly * Cloud infrastructure experience (Azure/AWS/GCP) * Hands-on fluency with AI-assisted development workflows (Claude Code, Codex, OpenCode); able to meet vibe-coding departments where they are ## Description About this position: As the Spark Team Engineer, you will be the technical half of SPARK, Arkana's two-person embedded unit that owns the front of our AI-native development funnel. You will build the proofs of concept that decide what Arkana makes next, real enough that the answer is trustworthy and fast enough that the answer arrives in weeks, and you will do the data work most of those answers turn on. This is deliberately a hands-on individual contributor role: there is no team to delegate to, and it stays that way by design. Working alongside the Spark Team Product Manager on focused 2-to-4-week engagements across departments, you will help close every engagement with a documented decision: advance, return, or kill. Engagements are short and embedded, so you will need to interface well with people you just met, work alongside non-technical builders with patience and without condescension, and capture how a department actually operates in days, not weeks. Seniority is dictated by the candidate: the mandate is fixed, and the level, scope, and expectations that come with it are calibrated to the person who takes it. PoC & Data Engineering: * Build timeboxed proofs of concept designed to answer a specific business question * Prepare Advanced concepts for handoff to the standardized deploy pipeline * Own the data layer of every engagement: find and assess source data, build the pipelines and models a POC needs, and judge early whether the data can support the idea at all Discovery & Engagement: * Share the discovery work: sit with end users, absorb departmental process knowledge quickly, and turn what you hear into technical shape * Assess feasibility, integration surface, and PHI/data boundaries during idea vetting * Evaluate existing vibe-coded applications and/or problem statements during engagement zero and advance/return/kill triage * Set the technical guardrails (data boundaries, access, non-goals) attached to Return decisions * Document decisions and transfer knowledge at every engagement close * Other duties as assigned Communication & Collaboration: * Genuine skill with non-engineers: draws out process knowledge patiently, explains technical findings without translation loss * Patience and care working alongside non-technical builders * Self-directed, comfortable without heavy process or oversight ## Related Videos - [Stop using Node.js like in 2020! 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