Actualizado: 9 jul 2019
Supply chain management company
Buenos Aires – Palermo or Remote
We're looking for a server side Data Engineer to join our client.
· Strong battle-tested data management and data integrations experience
· You are amazing at speaking the techno-functional talk with your business colleges, can understand the customer’s data.
· Prioritize action and rapid iteration over planning and perfection
· Flexible and comfortable working in a fast-paced and evolving environment
· Good command / proficient in spoken and written English
· Experience supporting and working with cross-functional teams in a dynamic environment
· Nice to have:
· Domain expertise in supply chain (4PL, 3PL, Logistics, Manufacturing, Inventory), with focus on integrations
· Experience with search engines and document-oriented databases
· Experience with AWS, SaaS startup experience are strong pluses
· RESTful web services experience
· 5+ years of experience with:
· Integration technologies such as APIs, Web Services and other ETL tools to process EDI messages, flat files, JSON, XML etc.
· Relational databases to develop stored procedures, triggers, and functions to enrich customer data (MySQL expertise is preferred).
· Integration tools such as Dell Boomi, Sterling Integrator, or equivalent
· Nice to have a bachelor degree in Computer Science, Technology or equivalent
· You'll be a critical member of a full-stack data engineering team focused on creating our data acquisition and management solution for supporting customer and partner data onboarding.
· Collaborate closely with your business and engineering team colleagues for acquiring, analyzing, mapping, and processing customer data
· Analyze data quality and mappings needed for processing different entities impacting large datasets
· Implement data integrations pipelines for addressing customers needs using different integrations technologies and tools
· Troubleshoot data acquisition processes and solutions and provide meaningful feedback for improving data acquisition, ingestion, validation, and persistence satisfying replay and data quality requirements