Senior Data Platform Engineer for AI‑Powered Analytics

Entellux group; México; Híbrido; MXN 900.000 - 1.500.000; Jornada completa

Descripción de la vacante

Entellux group is seeking an experienced data platform engineer to design and implement enterprise-grade data platforms powering analytics, ML, GenAI, and reporting. You will own end-to-end components—from ingestion to governance—working with a small cross-functional team across client environments.

Ideal candidates have 5+ years in data platforms, cloud-native architectures, and a hands-on approach to building scalable pipelines. Hybrid work and client-facing collaboration are part of the role.

Formación

• 5+ years of experience building enterprise data platforms.
• Experience with cloud-native data architectures and production-grade data pipelines.
• Ability to discuss trade-offs with clients and stakeholders.

Responsabilidades

• Design and build scalable batch and real-time data platforms.
• Own architecture: ingestion, orchestration, lineage, monitoring, governance, security.
• Develop ETL/ELT pipelines across cloud and hybrid landscapes.
• Integrate ERPs, CRMs, APIs, and streaming systems.
• Build data products for analytics, ML, and GenAI.
• Maintain data lakes/warehouses/Lakehouse platforms.
• Run production workloads with observability and cost controls.
• Produce production-grade data platforms and mentor engineers.

Conocimientos

Python

SQL

Data modeling

Data governance

Educación

Bachelor's degree in a related field

Herramientas

BigQuery

Dataflow

Pub/Sub

Cloud Composer (Airflow)

Vertex AI integrations

Descripción del empleo

Entellux group is seeking an experienced data platform engineer to design and implement enterprise-grade data platforms powering analytics, ML, GenAI, and reporting. You will own end-to-end components—from ingestion to governance—working with a small cross-functional team across client environments.

Ideal candidates have 5+ years in data platforms, cloud-native architectures, and a hands-on approach to building scalable pipelines. Hybrid work and client-facing collaboration are part of the role.