En Protecso, ofrecemos soluciones de negocios en Outsourcing TI, Managed Services, DevOps as a Service, Soluciones Cloud, Desarrollo Web y Mobile, Automatización de Procesos, Blockchain & IoT, Integración de Sistemas, Business Analytics, HubSpot, LeanFlows. Estamos guiados por valores, que aman lo que hacen y saben que todo es posible. En esta oportunidad nos encontramos en la búsqueda de profesionales para el cargo de:
✅ ROLE AND RESPONSIBILITIES:
AI-AUGMENTED PIPELINE DEVELOPMENT & AUTOMATION
- Develop, construct, and maintain large-scale data processing systems that collect data from a variety of structured and unstructured sources — using AI code generation tools to accelerate pipeline authoring, reduce boilerplate, and improve code quality.
- Build and optimize ELT pipelines using AI-assisted tooling to identify bottlenecks, suggest optimizations, and automate routine pipeline maintenance tasks.
- Identify, design, and implement internal process improvements: use AI to automate manual processes, optimize data delivery, and re-design infrastructure for greater scalability — replacing manual analysis with AI-driven discovery of improvement opportunities.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from various sources; use AI to accelerate infrastructure-as-code authoring and configuration.
AI-READY DATA PREPARATION & ML ENABLEMENT
- Prepare data for data scientist exploration and discovery using AI-assisted data profiling and quality assessment tools — surfacing anomalies, schema drift, and data gaps faster than manual inspection allows.
- Perform data wrangling and munging for downstream analytics and machine learning; leverage AI tools to generate and validate transformation logic against business rules.
- Assemble large, complex datasets that meet functional and non-functional business requirements; use AI to rapidly evaluate dimensional modeling approaches and ontology alignment strategies.
- Enable large-scale machine learning by designing and maintaining annotated datasets, elastic search approaches, and scalable data lake structures that support AI/ML workloads.
ANALYTICS PIPELINE & INSIGHT GENERATION
- Create and maintain analytics pipelines that generate data and insight to power business decision-making; use AI-assisted analysis to proactively surface trends, anomalies, and opportunities within pipeline outputs.
- Collaborate with data scientists, analysts, and business stakeholders on requirements for dimensional modeling, distributed ETL pipelines, and cross-repository data migration.
- Evaluate, compare, and improve design patterns, data lifecycle approaches, and data ontology alignment — using AI to model trade-offs and accelerate proof-of-concept validation.
- Work with data and analytics experts to continuously improve the functionality, reliability, and intelligence of data systems.
ROOT CAUSE ANALYSIS & QUALITY MANAGEMENT
- Perform root cause analysis on internal and external data and processes using AI-assisted investigation tools — replacing slow, manual log and lineage review with faster, AI-accelerated diagnostics.
- Develop and maintain data quality frameworks; use AI to automate anomaly detection, schema validation, and data contract enforcement across pipelines.
- Develop a strong understanding of company domains, strategic direction, and user needs to ensure data systems are aligned to business outcomes, not just technical requirements.