Job Opportunities API

About ShopGrok ShopGrok is a fast-growing, bootstrapped SaaS company providing leading retailers and consumer brands with real-time competitive price intelligence and product insights. We track millions of price points every week, processing massive datasets to power analytics that drive critical pricing decisions. We run a lean, high-performing team that prioritises engineering pragmatic solutions over bureaucracy. About the Role At ShopGrok, data is at the core of everything we build. We have recently built our modern data architecture (our “Bedrock” Platform) and are mid-way through migrating our enterprise customers across to it. In this role, you will work across both data platform engineering and data operations. A key objective is to shift operational effort into the Bedrock Platform by driving efficiency, automation, scalability and AI readiness. There will be an active maintenance element supporting customers on our Legacy Platform for at least the next 12 months. Success in this role means striking the right balance: keeping the legacy engine running reliably while dedicating focused effort to building out the new architecture and migrating customers across. We need an engineer who is comfortable with the imperfect nature of a legacy environment, pragmatic enough to pick the low-hanging fruit in a lean team, and skilled at converting legacy SQL workflows into clean, automated Bedrock pipelines. Key Responsibilities 1. Data Architecture & Automation Modern Data Architecture: Build out and refine our next-generation Bedrock Platform, utilising a Medallion Data Architecture (Bronze, Silver, Gold layers) to structure scalable data models. Transparent Lineage & Layered Testing: Establish transparent data lineage across all pipelines and design automated test suites at each layer of the data architecture to ensure end-to-end data quality. Platform Automation: Automate operational tasks and build resilient data infrastructure to eliminate repetitive break-fix work and prevent recurring issues. SDLC Practices: Apply modern software development practices (git version control, modular code, pull requests, continuous testing) to data pipelines. 2. Legacy Maintenance & Migration (6 to 12 Months) Balancing Priorities: Successfully balance ongoing maintenance and bug fixes on the Legacy Platform with dedicated build time for the new architecture. Legacy Code Wrangling: Dive into less structured legacy SQL logic and Alteryx ETL workflows, unpicking complex data pipelines to troubleshoot discrepancies or alter logic. Pragmatic Prioritisation: Comfortably navigate imperfect legacy code, identifying and executing on low-hanging fruit to deliver immediate reliability wins without getting bogged down. Platform Migration: Systematically refactor legacy datasets and logic into the Bedrock Platform as customers are transitioned across. 3. Data Operations & Quality Ensure high data quality and accuracy across incoming raw data, intermediate transformations, and outgoing analytical models. Trace and resolve data anomalies quickly across collection, transformation, and delivery stages.