#136209 - Data Engineer - HR Analytics & AI-Ready Data

Lifted Solutions Inc.; Bogotá ciudad; Presencial; COP 179.463.000 - 314.060.000; Jornada completa

Descripción de la vacante

Lifted Solutions Inc. seeks an experienced Data Engineer to build secure, scalable data pipelines, warehouse models, and analytics datasets for people insights.

Enterprise experience is strongly preferred, with hands-on Snowflake, dbt, Python, and Airflow skills. You will design semantic layers and governed data experiences, integrate REST APIs, and ensure robust data quality while maintaining strong documentation and security practices.

Formación

• 5+ years of relevant experience.
• Hands-on Snowflake experience, including data modeling, datamarts, and data warehouse design.
• Hands-on dbt experience for data transformations.
• Strong Python experience, including object-oriented programming and data scripting.
• Hands-on Airflow experience for pipeline orchestration.
• Experience integrating REST APIs and ingesting data from external sources.
• Hands-on Google BigQuery querying and optimization experience.
• Experience securely handling sensitive data at large scale.
• Experience with real-time or near-real-time data processing from APIs, Google Sheets, or comparable sources.
• Strong SQL skills, including highly optimized queries.
• Comprehensive technical documentation skills.
• Advanced English communication skills.

Responsabilidades

• Develop and maintain secure, efficient data pipelines and warehouse models.
• Build ETL infrastructure using Python, dbt, Terraform, AWS Glue, EMR, and S3.
• Integrate data from APIs, cloud systems, Google Sheets, and other sources.
• Create and maintain Snowflake warehouse models and datamarts.
• Develop automated data-quality tests and improve data-engineering processes.
• Monitor production pipelines and target 99.5% uptime.
• Design semantic views, ontology layers, and certified metrics over warehouse models.
• Build governed data experiences using LLM-native query layers.
• Configure secure Model Context Protocol connections for data sources and AI tooling.
• Document data models, pipelines, and technical decisions comprehensively.

Conocimientos

Snowflake

dbt

Python

Airflow

REST APIs

BigQuery

SQL

Data security

Real-time data

Documentation

English

Herramientas

Snowflake

dbt

Apache Airflow

Google BigQuery

Terraform

AWS Glue

Amazon EMR

S3

REST APIs

Descripción del empleo

Job Description

Summary

We are seeking an experienced Data Engineer to build and maintain secure, reliable, and scalable data pipelines, warehouse models, and analytical datasets supporting people insights. This role combines hands-on data engineering with data modeling, platform reliability, semantic-layer design, and governed access for both business intelligence tools and AI-enabled interfaces.

Enterprise experience strongly preferred.

Key Responsibilities

• - Develop and maintain secure, efficient data pipelines using dbt, PySpark, and Python applications.
• - Build extraction, transformation, and loading infrastructure using Python, dbt, Terraform, AWS Glue, Amazon EMR, and Amazon S3.
• - Integrate data from APIs, cloud systems, Google Sheets, and other structured sources.
• - Create and maintain Snowflake warehouse models, datamarts, and analytics-ready datasets.
• - Develop automated data-quality tests and improve internal data-engineering processes.
• - Monitor production pipelines and help maintain a 99.5% uptime objective.
• - Design semantic views, ontology layers, business-friendly entities, relationships, and certified metrics over warehouse models.
• - Build governed natural-language data experiences using Snowflake Cortex Analyst, Cortex Search, or equivalent LLM-native query layers.
• - Configure secure Model Context Protocol connections or comparable interfaces between governed data sources and internal AI tooling.
• - Document data models, pipelines, business logic, operational procedures, and technical decisions comprehensively.

Qualifications

Must-Have Skills

• - 5+ years of relevant experience.
• - Hands-on Snowflake experience, including data modeling, datamarts, and data warehouse design.
• - Hands-on dbt experience for data transformations.
• - Strong Python experience, including object-oriented programming and data scripting.
• - Hands-on Airflow experience for pipeline orchestration.
• - Experience integrating REST APIs and ingesting data from external sources.
• - Hands-on Google BigQuery querying and optimization experience.
• - Experience securely handling sensitive data at large scale.
• - Experience with real-time or near-real-time data processing from APIs, Google Sheets, or comparable sources.
• - Strong SQL skills, including highly optimized queries.
• - Comprehensive technical documentation skills.
• - Advanced English communication skills.

Nice-to-Have Skills

• - Experience designing semantic layers or semantic models that provide business-object abstraction over dbt and warehouse models.
• - Experience with Snowflake Cortex Analyst, Cortex Search, or an equivalent LLM-native query layer.
• - Experience with Model Context Protocol or a similar tool-calling and context-exposure framework.
• - Familiarity with prompt and context engineering for grounding AI agents in certified data sources.

Additional Information

Required Tools & Platforms

• - Snowflake.
• - dbt.
• - Python and PySpark.
• - Apache Airflow.
• - Google BigQuery.
• - SQL.
• - REST APIs.
• - Terraform.
• - AWS Glue, Amazon EMR, and Amazon S3.

Location, Time & Engagement

• - Candidates must be based in an eligible LATAM location.
• - Full US Central Time coverage is required.
• - This is a contract engagement at 40 hours per week.
• - The anticipated engagement runs through March 31, 2027.
• - This is not currently a contract-to-hire opportunity.