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Open nowFirst seen 2 days ago

Data Engineer SSR

TalentCross224 open roles

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Your applicationOpen nowData Engineer SSRTalentCross

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on TalentCross's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. TalentCross postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 2 days ago

TalentCross median: 1 days open

The posting

DATA ENGINEER

Detalles de la Contratación

  • Esquema de trabajo: Híbrido (2 días presenciales en oficinas de Parque Patricios, CABA / 3 días remoto).
  • Modalidad de contratación: Contractor (Servicios profesionales).

Propósito del rol

Diseñar, desarrollar y optimizar la infraestructura y flujos de datos de la compañía, garantizando la disponibilidad, calidad y trazabilidad de la información para dar soporte a soluciones de Business Intelligence, Analítica Avanzada e Inteligencia Artificial.

Responsabilidades principales

  • Pipelines & ETL/ELT: Diseñar, desarrollar y orquestar flujos de datos eficientes integrando múltiples fuentes y sistemas.
  • Modelado de Datos: Construir y mantener datamarts y estructuras analíticas orientadas a la explotación operativa, táctica y estratégica.
  • Soporte a BI e IA: Preparar y estructurar datasets optimizados para la creación de tableros, analítica y entrenamiento de modelos de IA.
  • Calidad y Gobierno: Velar por la consistencia, trazabilidad y limpieza de los datos en todo su ciclo de vida.
  • Colaboración Técnica: Trabajar en conjunto con Arquitectura de Datos y de Soluciones para definir e implementar mejores prácticas, estándares y escalabilidad.

Requisitos e Historia Técnica

  • SQL: Nivel avanzado (excluyente).
  • Programación: Experiencia sólida con Python para procesamiento e integración de datos.
  • Bases de Datos: Manejo práctico con PostgreSQL u otros motores relacionales/analíticos.
  • Orquestación & ETL: Experiencia en la construcción de pipelines y herramientas de orquestación (idealmente Apache Airflow).

Deseables (Plus)

  • Experiencia con herramientas de visualización o BI (idealmente Apache Superset).
  • Conocimiento o experiencia en entornos Cloud (AWS, GCP o Azure).
  • Integración a través de APIs y consumo de servicios.
  • Nociones de gobernanza y calidad de datos.

Competencias clave

  • Fuerte capacidad analítica y orientación a la calidad técnica.
  • Criterio enfocado en la escalabilidad y mantenibilidad del código/estructuras.
  • Trabajo en equipo y comunicación fluida con células de Desarrollo, BI e IA.
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  1. A CV for this posting

    Written against TalentCross's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on TalentCross's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    TalentCross's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

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  6. The interview in your calendar

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    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
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Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

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The numbers game

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