📌 Position: Senior Data Engineer Location: Remote from LATAM Contract Type: Full-time vendor Time Zone Alignment: EST (±2 hours overlap) 🧭 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. 🚀 Project Overview This role is embedded within a centralized Human Resources Data Mart (HRDM) engineering team, specifically supporting the Analytics product area.

The primary objective is to maintain a secure, high-quality HR data warehouse that powers workforce analytics across international enterprise Centers of Excellence (COEs) and executive leadership. As a Senior Data Engineer, you will build data pipelines and cloud infrastructure using dbt, AWS, Snowflake, and BigQuery, bridging traditional data architecture with modern AI capabilities.

You will construct a dbt-based semantic layer and establish Model Context Protocol (MCP) and Snowflake Cortex workflows, enabling business leaders to query certified workforce data via natural-language AI agents. 🔍

Key Responsibilities

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Data Pipeline Engineering & ETL/ELT

Develop, optimize, and maintain secure data pipelines using dbt, PySpark, Python, and Apache Airflow to ingest HR data sources from REST APIs, real-time streams (e.g., Google Sheets, web APIs), and external platforms. -

Infrastructure & Cloud Resource Tooling

Provision, configure, and maintain scalable infrastructure for extraction, transformation, and loading processes utilizing Terraform, AWS Glue, AWS EMR, and AWS S3. -

Data Warehouse & Data Mart Modeling

Design and maintain optimized data models, data marts, and warehouse structures across Snowflake and Google BigQuery. -

Semantic Layer & Ontology Architecture

Build semantic views and ontology layers (mapping CORE → SEMANTIC → METRICS) on top of dbt models to provide business-friendly entity abstractions for BI tools and LLM agents. -

AI Agent & MCP Deployment

Configure and deploy generative AI query agents using Snowflake Cortex (Cortex Analyst, Cortex Search) and maintain MCP (Model Context Protocol) connections between Snowflake and internal AI tools for secure, natural-language data querying. -

Pipeline Monitoring, Quality & Compliance

Monitor data pipelines to enforce 99.5% uptime, build automated tests within a Data Quality Framework, ensure secure handling of sensitive data (PII), and produce comprehensive technical documentation. 💡

Must-Have Skills

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Experience Level

5+ years of dedicated, hands-on data engineering experience. -

Data Warehousing & Transformation

Deep expertise in Snowflake (data modeling, datamarts, warehouse design), Google BigQuery (querying and optimization), and dbt (data transformations). -

Programming & Ingestion

Strong object-oriented Python scripting capabilities and hands-on experience with REST API integrations and real-time data ingestion. -

Orchestration & Querying

Proficiency in Apache Airflow for pipeline orchestration and advanced, highly optimized SQL writing skills. -

Governance & Security

• Demonstrated experience in the secure handling of large-scale, sensitive data (PII) and writing comprehensive technical documentation.
• - Experience working in Agile teams and remote, distributed environments.
• - Advanced/Fluent English communication skills for daily interaction. 🌟 Nice-to-Have Skills -

Semantic Layer Design

Experience in semantic modeling design to provide business-object abstractions over dbt and warehouse models. -

LLM-Native Query Layers

Hands-on experience with Snowflake Cortex (Cortex Analyst, Cortex Search) or equivalent LLM query frameworks. -

Agentic Frameworks

Exposure to MCP (Model Context Protocol) or similar tool-calling and context-exposure frameworks. -

Context Engineering

Familiarity with prompt and context engineering to ground AI agents in certified enterprise data sources. 🌐 Time Zone & Collaboration The role requires collaboration with teams aligned to US Eastern Standard Time (EST). Flexibility to overlap a minimum of 4 core working hours with US time zones is expected. 💬 Language All interviews, documentation, and daily communication will be in English. #LI