Posted 5 days ago
Data Engineer (Architect) - 1895
AI Summary
Data Architect responsible for defining the long-term data strategy, designing and optimizing complex data models, leading database performance tuning, and establishing data governance practices for a high-visibility initiative.
About this role
๐งญ 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.
๐ 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.
๐ 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.
๐ก 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.
๐ 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.
๐ Time Zone & Collaboration
The role requires collaboration with teams aligned to Central Time (CT), USA. Candidates must overlap at least 4โ5 hours daily with US-based stakeholders to ensure seamless architectural alignment.
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