Responsabilidades

🤓 Como Data Engineer, la empresa espera que realices las siguientes tareas:

Design, develop, and maintain ETL/ELT pipelines connecting multiple data sources (CRM, call tracking, and quality systems).
Build and manage data models, marts, and semantic layers that standardize KPI logic and enable unified reporting.
Prepare and maintain structured, anonymized datasets for AI model training and validation.
Implement secure, tenant-aware data structures within AWS (RLS, LF-Tags, KMS).
Ensure data quality and governance through lineage documentation, metric catalogs, and validation testing.
Collaborate with DevOps and Compliance teams to align data-layer security with company standards.
Monitor pipeline performance and SLA adherence, resolving data accuracy or latency issues.
Deliver curated datasets to BI and engineering teams for dashboards and analytics.
Maintain detailed documentation across pipelines, models, and governance artifacts.
Continuously improve data workflows, schema evolution, and automation practices.

Requisitos

✨ Eres la persona que buscan si tienes..

4+ years of experience as a Data Engineer, BI Developer, or similar role.
Proficiency in Python and SQL for data transformation and automation.
Strong command of AWS services (S3, Glue, Athena, Lambda, Redshift Spectrum).
Hands-on experience with dbt (Core or Cloud) for modeling, testing, and documentation.
Experience integrating data from SaaS or CRM platforms (Lead Docket, Salesforce, HubSpot, etc.).
Strong understanding of data warehouse/lakehouse design, ETL/ELT workflows, and schema versioning.
Proven ability to execute independently while staying aligned with project priorities.
Excellent English communication skills, written and spoken.