📌 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
- 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
- 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.
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