Senior Software Engineer — Python-to-.NET Data Automation Migration - Ubiminds (548)

Info on the AI Analyst - Developer (Telemetry)(498) role   Ready to take the next step in your international career? We can support you! Ubiminds is a GPTW-certified, people-first company that partners with American software product companies to scale their global teams. We connect top LATAM talent with international product companies while providing full employer-of-record support and long-term career development. In this opportunity, you will join a global engineering organization undergoing an AI-native transformation, helping engineering teams adopt modern AI development workflows and significantly accelerate their productivity. This role combines hands-on engineering expertise, AI tooling mastery, and developer enablement, helping teams integrate AI-powered workflows into their daily development processes. Challenge We are looking for an AI Analyst - Developer Telemety who will be the measurement backbone of the AI Accelerator engagement.  This role builds and maintains the data infrastructure that makes the transformation visible -- turning raw signals from AI coding tools, GitHub, and CI/CD pipelines into executive-grade dashboards that track the Carpaccio Metric, identify Super-Builder candidates, and prove ROI in real time. This is not a generic data analyst role. It requires someone who understands how software gets built - how PRs move, how AI tools are actually used versus how they are configured, and what engineering productivity metrics actually tell you versus what they obscure. The ideal candidate is a data engineer or analytics engineer who has spent time inside an engineering organization and has strong opinions about what good developer productivity measurement looks like.   Responsibilities: Daily pipeline health checks and anomaly triage (first 30 minutes of each day) Weekly cohort analysis reports delivered every Monday to the Project Lead Maintain and update dashboard visualizations as new telemetry sources are onboarded Sync with AI Analyst - DevX to cross-reference quantitative signals against qualitative friction findings Attend weekly executive readouts to provide real-time data context when questions arise Train team members on dashboard interpretation on a rolling basis throughout the engagement Submit a weekly pipeline health digest to the Project Lead every Friday   Mandatory Skills: 4+ years in data engineering, analytics engineering, or a hybrid data/software role inside an engineering organization Demonstrated experience building production-grade data pipelines -- not just running queries, but owning the infrastructure that feeds dashboards Hands-on experience with GitHub API and CI/CD pipeline data (not just using GitHub, but extracting and processing its event stream) Prior exposure to developer productivity metrics, DORA metrics, or engineering KPI programs -- ideally as the person who built the measurement system, not just consumed it   Nice to Have: Experience at a SaaS company with a distributed engineering team of 50 or more engineers Familiarity with the Workday or Salesforce data ecosystem (the company integrates with enterprise HR and talent platforms) Prior work on an AI transformation or developer productivity initiative -- ideally one where you owned the measurement infrastructure Experience with real-time dashboarding and streaming data pipelines (Kafka, Kinesis, or equivalent)   Team & Environment: Distributed engineering teams across LATAM and the U.S. Highly collaborative environment focused on experimentation and innovation. Strong engineering culture centered on mentorship, knowledge sharing, and continuous improvement. Opportunity to shape AI-native engineering practices at scale. High visibility role working closely with engineering leadership. Experience designing internal engineering guilds, communities of practice, or centers of excellence. Experience building AI-enabled developer workflows in enterprise SaaS environments. Experience working in HR tech, AI platforms, o