Data Engineer (Architect) - 1895

In All Media Inc; Estado de México; Presencial; MXN 1.610.594 - 2.147.458; Jornada completa

Descripción de la vacante

A cutting-edge technology firm based in Mexico is seeking a Data Architect to lead the development of a robust data strategy and optimize data structures. The role demands expertise in SQL, data modeling, and database performance tuning, alongside proficiency in Python for automation tasks. Collaboration with international stakeholders is essential, requiring at least 4-5 hours of overlap with US-based teams. This is an opportunity to influence data quality and accessibility while driving impactful business decisions.

Formación

• Expert-level proficiency in SQL including query design and complex aggregations.
• Proven track record of designing scalable schemas.
• Deep knowledge of database performance tuning.

Responsabilidades

• Architect and implement the long-term data strategy.
• Design and optimize complex data models.
• Lead database performance tuning.
• Identify business-critical data points.
• Establish data governance practices.
• Utilize Python for automation tasks.
• Partner with teams to support business goals.

Conocimientos

Advanced SQL Mastery

Data Modeling

Optimization Expertise

Functional Python

Strategic Intuition

Self-Direction

Fluent English

Herramientas

Snowflake

dbt

Airflow

Descripción del empleo

🧭 About Inallmedia.com

Inallmedia.com is a global technology and design firm focused on building impactful digital solutions through remote, distributed teams across LATAM. We partner with international clients across industries, providing long-term technical expertise, product innovation, and team augmentation.

Our teams work on high-scale platforms that require strong engineering ownership, business alignment, and measurable product impact.

🚀 Project Overview (Project Outpost)

You will join a high-visibility initiative focused on maturing the organization's data landscape. The Outpost project is moving from an "evolving" data environment to a structured, high-performance ecosystem.

As a Data Architect, your mission is to solve current structural inconsistencies and define the long-term data strategy. This is not a "maintenance" role; it is an architectural leadership position meant to ensure data is reliable, accessible, and high-quality for both internal operational efficiency and external customer reporting. By improving schema performance and structure, you will directly enable better business decisions and robust application performance.

🔍 Key Responsibilities

• Define Data Strategy: Architect and implement the long-term data roadmap to transition the organization into a structured, high-performance ecosystem.
• Schema Design: Design and optimize complex data models for both transactional (operational) and analytical use cases.
• Performance Tuning: Lead database performance tuning and structural improvements to ensure high-speed query execution and system reliability.
• Identify Critical Insights: Use analytical intuition to independently identify business-critical data points and define clear analysis goals.
• Standardization: Establish and enforce organizational naming conventions, data governance practices, and structural consistency across the landscape.
• Automation: Utilize Python to create automation scripts for data exploration, cleaning, and landscape management.
• Cross-Functional Collaboration: Partner with Product, Backend Engineering, and Stakeholders to ensure data schemas support both business goals and application UX.

💡 Must-Have Skills

• Advanced SQL Mastery: Expert-level proficiency in query design, CTEs, window functions, and complex aggregations.
• Data Modeling: Proven track record of designing scalable schemas for diverse use cases (Transactional vs. Analytical).
• Optimization Expertise: Deep knowledge of database performance tuning and structural improvements.
• Functional Python: Proficiency in using Python (loops, functions, dictionaries) for data exploration and automation tasks.
• Strategic Intuition: The ability to navigate ambiguity and independently identify how data structure impacts business outcomes.
• Self-Direction: Proven ability to manage complex data landscapes and architectural shifts without constant supervision.
• Fluent English: Strong communication skills for daily collaboration with international stakeholders.

🌟 Nice-to-Have Skills

• Cloud Warehousing: Specific experience with Snowflake or similar modern cloud data warehouse environments.
• Governance: Experience implementing formal data governance frameworks and metadata management.
• ETL/ELT Optimization: Hands-on experience optimizing specific data transformation pipelines to reduce latency.
• Modern Data Stack: Familiarity with tools like dbt or Airflow for managing the data lifecycle.
• LATAM Experience: Experience working in remote, distributed teams across Latin American time zones.

🌐 Time Zone & Collaboration

The role requires collaboration with teams aligned to Central Time (CT), USA. Candidates must overlap at least 4–5 hours daily with US-based stakeholders to ensure seamless architectural alignment.