Data Engineer

Releady; Bogotá ciudad; Hybrid; COP 84,443,000 - 101,146,000; Full time

Job summary

Releady is partnering with a leading furniture and home furnishings retailer to hire a Data Engineer. This role focuses on building scalable data pipelines in a Microsoft Fabric and Azure environment, using Python and PySpark, to power analytics, ML, and BI across a growing retail footprint.

You'll collaborate with AI/ML engineers, BI teams, and stakeholders, contribute to modernizing the data platform, and ensure data quality, governance, and documentation.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• 5+ years experience as a Data Engineer or in backend/data-intensive systems.
• Expertise in ETL/ELT design and data integration.
• Proficiency in SQL and Python for data processing.
• Hands-on experience with the Microsoft stack: Fabric, Azure, Python, PySpark notebooks, Data Factory, Data Lakes, and SQL Server.
• Familiarity with medallion architecture (bronze, silver, and gold) and modern data warehouses.
• Knowledge of data modeling and version control (Git), and Agile tools (Jira, Confluence).
• Preferred: experience with AI/ML applications, SQL DB administration, and strong statistical fundamentals.

Responsibilities

• Design, build, and optimize ETL/ELT notebooks and pipelines for ingestion, transformation, and delivery of business-critical data.
• Implement medallion architecture to standardize data for downstream consumption.
• Automate data collection, processing, and reporting workflows to improve efficiency.
• Ensure high-quality, reliable data through validation, monitoring, troubleshooting, and performance tuning.
• Integrate APIs, data flows, and orchestration processes across the Microsoft ecosystem.
• Partner with AI/ML engineers, BI teams, developers, and business stakeholders to structure data for analytics and ML initiatives.
• Contribute to re-architecture and modernization of the data platform for scalability.
• Maintain documentation of data models, pipelines, and integrations.

Skills

Data Engineering

ETL/ELT design

SQL

Python

Azure Fabric

Medallion Architecture

Git

Jira & Confluence

Data Modeling

AI/ML experience

Education

Bachelor's degree in CS/Engineering

Tools

Data Factory

Data Lakes

SQL Server

PySpark

Microsoft Fabric

Azure

Job description

OVERVIEW

Releady is partnering with a leading furniture and home furnishings retail company to hire a Data Engineer. This organization is the top-selling furniture brand in North America and is undergoing an AI-first technology transformation, modernizing its data platform to support advanced analytics, machine learning, and business intelligence across a growing retail footprint. The role sits within a Technology and AI Center of Excellence spanning cloud, data, security, and automation.

In this role, you will design, build, and maintain scalable, high-performance data pipelines and infrastructure that power the company's analytics and machine learning initiatives. The work operates primarily within a Microsoft Fabric and Azure ecosystem, driven by Python and PySpark. You will collaborate closely with AI/ML engineers, BI teams, developers, and business stakeholders to ensure data is reliable, accessible, and optimized for downstream use, while contributing directly to the re-architecture and modernization of the company's data platform.

• Employment Type: Full-Time Contract
• Location: Remote
• Compensation: $2,600 USD / month
• Schedule: Monday-Friday, 40 hours/week; occasional after-hours or weekend work to support deployments.

RESPONSIBILITIES

Data Pipeline Development & Management

• Design, build, and optimize ETL/ELT notebooks and pipelines for ingestion, transformation, and delivery of business-critical data.
• Implement medallion architecture (bronze, silver, and gold layers) to standardize data for downstream consumption.
• Automate data collection, processing, and reporting workflows to improve efficiency and reduce manual effort.
• Ensure high-quality, reliable data through validation, monitoring, troubleshooting, and performance tuning.
• Integrate APIs, data flows, and orchestration processes across the Microsoft ecosystem.

Collaboration & Analytics Enablement

• Partner with AI/ML engineers, BI teams, developers, and business stakeholders to structure data for analytics, forecasting, and ML initiatives.
• Contribute to the re-architecture and modernization of the company's data platform for scalability and business alignment.
• Maintain clear documentation of data models, pipelines, and integrations for transparency and knowledge sharing.

Data Quality & Governance

• Implement systems to monitor data quality, ensure data integrity, and enforce security standards.
• Audit, track, and improve data processes to comply with organizational standards and regulatory requirements.
• Support version control, Agile workflows, and best practices using Git, Jira, and Confluence.

QUALIFICATIONS

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience as a Data Engineer or in backend or data-intensive systems.
• Expertise in ETL/ELT design, data integration, and pipeline orchestration.
• Proficiency in SQL and Python for data processing and automation.
• Hands-on experience with the Microsoft stack: Fabric, Azure, Python, PySpark notebooks, Data Factory, Data Lakes, and SQL Server.
• Familiarity with medallion architecture (bronze, silver, and gold) and modern data warehouse practices.
• Knowledge of data modeling, version control (Git), and Agile tools (Jira, Confluence).
• Preferred: experience with AI/ML applications, SQL database administration, and a strong statistical foundation to support data-driven modeling.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other non-merit factor. We are committed to creating a diverse and inclusive environment for all employees.