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

Lifted (an Upwork Company); Colombia; Remote; COP 267,530,000 - 423,589,000; Full time

Job summary

Lifted (an Upwork Company) is seeking an experienced Data Engineer to design and maintain secure, scalable data pipelines and analytics-ready datasets supporting people insights. This role blends hands-on engineering with data modeling, platform reliability, semantic-layer design, and governed access for BI tools and AI-enabled interfaces.

You will work with Snowflake, dbt, Python, PySpark, and Airflow to build warehouse models, data quality tests, and governed AI-ready data experiences.

Qualifications

• 5+ years of relevant data-engineering experience.
• Snowflake data modeling, datamarts, and warehouse design.
• dbt experience for data transformations.
• Strong Python experience with OOP.
• Airflow experience for pipeline orchestration.
• Experience with REST APIs and external data ingestion.
• BigQuery querying and optimization.
• Secure handling of large-scale sensitive data.
• Real-time or near-real-time data processing.
• Strong SQL and highly optimized queries.
• Excellent technical documentation skills.
• Advanced English communication skills.

Responsibilities

• Develop and maintain secure, efficient data pipelines.
• Build ETL using Python, dbt, Terraform, AWS services.
• Ingest data from APIs, cloud systems, and Google Sheets.
• Create Snowflake warehouse models and datamarts.
• Develop data-quality tests and improve processes.
• Monitor pipelines to maintain uptime.
• Design semantic views, ontology layers.
• Build governed data experiences with LLM-native interfaces.
• Configure secure data-source interfaces for internal AI tooling.
• Document data models, pipelines, and decisions comprehensively.

Skills

5+ years experience

Snowflake data modeling

dbt data transformations

Python / PySpark

Airflow orchestration

REST API data ingestion

BigQuery querying

security of sensitive data

real-time data processing

SQL optimization

technical documentation

English communication

Tools

Snowflake

dbt

Python

PySpark

Airflow

Google BigQuery

REST APIs

Terraform

AWS Glue / EMR

S3

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.

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.

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.