Senior Data Engineer

Fusion Worldwide is a global open market distributor of electronic components operating a production data and intelligence platform for supply chain and trading operations. The Senior Data Engineer will build and maintain data pipelines, object models, quality controls, APIs, applications, system-of-record write-backs, and production AI agent workflows. The role also involves end-to-end feature delivery, performance engineering, incident response, and creating explainable, auditable systems.

Responsibilities:

• Work with the object model covering companies, parts, offers, and demand signals. That includes adding object types, properties, and relationships as the data needs them
• Build and maintain ingestion from RMS, Azure SQL, HubSpot, and vendor APIs, along with the transforms, pipelines, and automations behind it
• Build and maintain the quality gates, including data expectations that fail the build, freshness checks against declared SLAs, and tests that catch problems nobody would otherwise notice
• Tune performance across query plans, index design, materialization strategy, and caching
• Help with incident response when pipelines or write-backs break, which may include on-call
• Work on the write-back path into RMS. Scores, enrichment, resolved entities, and operational flags get written back to the system of record
• Handle idempotency, conflict handling, and reconciling the two sides when they disagree
• Design the APIs that UIs in Web RMS use to pull platform data. You work on the contracts and the versioning, and you make sure the APIs are fast enough for a UI
• Build custom applications
• Build agent workflows that read the object model and act on it, such as triaging inbound RFQs, picking out pricing signals, and flagging anomalies in offers
• Build and maintain the agent setup the team develops with, including instructions, tool connections, and the checks on agent output

Requirements:

• Production data platform experience, on platforms such as Databricks, Snowflake, Spark, or dbt
• 8+ years building software, weighted toward backend and data engineering
• Expert SQL and deep experience with relational databases such as SQL Server, PostgreSQL, Oracle, or MySQL
• You can read an execution plan, design indexes that hold up under load, and tell when a normalized model is the wrong choice
• Experience writing back into a system of record. Transactional integrity, idempotency, and reconciliation
• API design. You've designed APIs for applications you don't control, changed them without breaking those applications, and shaped them around what a UI needs
• End-to-end delivery. You can point to features you drove from idea through POC, build, iteration, and release
• Cashing and performance engineering. You've made slow things fast and can explain what you changed
• Git, code review, and CI/CD. You work in Git, review other people's code, and ship through automated tests in a CI/CD pipeline
• Data governance and security. Access controls, handling sensitive data, and meeting audit requirements
• Production LLM systems you built and shipped, including what comes after shipping, such as evaluation, guardrails, cost, and latency
• Day-to-day work with AI agents on production systems, with specifics on where they help and where they quietly fail
• Building systems other people can audit. Lineage that holds up, parameters stored as versioned data, and outputs a non-engineer can challenge
• Clear written communication. We write a lot of documents, and this role writes many of them
• 3+ years hands-on experience with a production data platform, including object modeling, building and shipping pipelines, and shipping an application that people use
• Python and PySpark, including catching what an agent gets wrong, such as a transform that looks right but skews the join, a window function that silently drops rows, or a fix that passes tests and breaks the contract downstream
• Dimensional modeling and schema design judgment
• Entity resolution, master data, taxonomies, or knowledge graphs
• React
• Process mining
• Jira, including connecting to it with Claude or other AI tools
• ERP integration experience
• Streaming and event-driven ingestion (Kafka, CDC)
• Electronics distribution, supply chain, or industrial B2B data