We're seeking a Lead Data Engineer to come aboard and strengthen our team. Among all engineering positions tied to this engagement, this one carries the heaviest data responsibility. Should any pipeline lose data, positions shift out of alignment, or signals miscalculate, the entire calibration and UAT process collapses. Nothing else can function properly unless accuracy and operational resilience are locked in here first.ResponsibilitiesCarry out every database migration set across the Unified Data Store so that schema alignment remains intact throughout the platformConstruct and sustain the complete collection of Source Adapters that link outside systems into the broader data platformBuild out the Field Mapper, setting up field bindings specific to each project and franchise that standardize source system data into the unified schema upon intakeDevelop the Link Resolver, tasked with connecting CL-to-ticket, ticket-to-ticket, and case-to-defect/requirement relationships spanning every source family,



supplying input directly to the Attribution ResolverConstruct the Attribution Resolver to map the change-ticket-area-test pathway, together with the Counted Signals Aggregator, which generates file-to-area and area-to-area association tables complete with path standardization and count validationAssemble the Area Vocabulary along with its related Translation Tables to maintain uniform area categorization throughout the systemCreate the complete set of Signal Catalogue computation jobs addressing all eight primary signals — area fragility, recency, recent failures, change-touch, coupling, windowed area change volume, testing alignment, validation recency, and defect impact/volume/age — with provenance tracking built into eachTake charge of writing the data dictionary for every storage element, updating it progressively as new functionality rolls outRequirementsFive-plus years of direct, practical experience in Python software developmentA minimum of one year spent leadin

📌 Lead Data Engineer (Perú)
🏢 EPAM Systems
📍 Perú