Data Warehouse Engineer

Tires Easy; Argentina; Remote; ARS 136,430,000 - 197,065,000; Full time

Job summary

Tires Easy is seeking a Data Warehouse Engineer to design, build, and optimize scalable data infrastructure in a largely cloud-based environment. You will develop ETL/ELT pipelines, assure data quality, and collaborate with analysts and engineers to translate business needs into efficient data solutions.

You will work in an entrepreneurial setting, focusing on learning customer needs and improving data-driven decision-making, while maintaining high standards of technical excellence and

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related technical field (Master’s preferred).
• 3+ years of experience designing, developing, and maintaining data warehouses and ETL/ELT workflows in production environments.
• Proficiency in SQL and strong experience with data modeling, schema design, and performance optimization.
• Proven hands-on experience with modern data engineering tools (e.g. Airflow, dbt) and AWS cloud-based data platforms (e.g., Snowflake, Redshift).
• Hands-on experience (on business projects) with programming languages such as: Python, C/C++/Java.
• Strong analytical and problem-solving skills, with the ability to work collaboratively across cross-functional teams in a fast-paced, data-driven environment.
• Must not have had any disciplinary actions regarding attendance, conduct and/or performance in the past 90 days, and must not be approaching such action.

Responsibilities

• Design, build, and maintain scalable, high-performance data warehouse solutions using modern cloud and on-premise technologies.
• Develop, schedule, and monitor robust ETL/ELT pipelines using tools such as Apache Airflow for orchestration and dbt for data transformation.
• Optimize data models, queries, and storage strategies to improve performance, scalability, and system reliability.
• Implement and enforce data quality, validation, and governance standards to ensure accuracy, consistency, and compliance.
• Collaborate with data analysts, engineers, and business stakeholders to translate analytical requirements into efficient data solutions.
• Continuously enhance and automate data workflows by leveraging Airflow, dbt and other modern frameworks to drive efficiency and continuous improvement.
• AWS Linux controls for DW setup

Education

Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related technical field

Master’s degree preferred

Tools

Airflow

dbt

Snowflake

Redshift

Job description

We’re on a mission to change the tire industry — how it’s delivered and how it’s experienced. A pioneer in the automotive e-commerce industry, we take pride in our extensive selection of top-name brands and budget-friendly options, ensuring our customers find the perfect tire to suit their needs. As a part of our growing and dynamic team, you'll contribute to our commitment to exceptional service, innovation, and customer satisfaction. Embrace the opportunity to be a driving force behind one of the fastest growing e-commerce companies in the US.

SUMMARY:

We are seeking a skilled and detail-oriented Data Warehouse Engineer to join our Business Intelligence team and play a key role in designing, building, and optimizing our data infrastructure. In this role, you will develop and maintain scalable data pipelines, ensure the accuracy and performance of our warehouse systems, and collaborate closely with analysts, engineers, and stakeholders to support data-driven decision-making across the organization. You will be instrumental in driving data quality, reliability, and efficiency, while fostering a culture of technical excellence and continuous improvement.

As a member of our team, you will work in an entrepreneurial environment where we are constantly looking to learn what our customers need and to develop better ways to serve them.

Resume must be submitted in English.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Design, build, and maintain scalable, high-performance data warehouse solutions using modern cloud and on-premise technologies.
• Develop, schedule, and monitor robust ETL/ELT pipelines using tools such as Apache Airflow for orchestration and dbt for data transformation.
• Optimize data models, queries, and storage strategies to improve performance, scalability, and system reliability.
• Implement and enforce data quality, validation, and governance standards to ensure accuracy, consistency, and compliance.
• Collaborate with data analysts, engineers, and business stakeholders to translate analytical requirements into efficient data solutions.
• Continuously enhance and automate data workflows by leveraging Airflow, dbt and other modern frameworks to drive efficiency and continuous improvement.
• AWS Linux controls for DW setup

QUALIFICATION REQUIREMENTS

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related technical field (Master’s preferred).
• 3+ years of experience designing, developing, and maintaining data warehouses and ETL/ELT workflows in production environments.
• Proficiency in SQL and strong experience with data modeling, schema design, and performance optimization.
• Proven hands‑on experience with modern data engineering tools (e.g. Airflow, dbt) and AWS cloud-based data platforms (e.g., Snowflake, Redshift).
• Hands‑on experience (on business projects) with programming languages such as: Python, C/C++/Java.
• Strong analytical and problem‑solving skills, with the ability to work collaboratively across cross‑functional teams in a fast‑paced, data‑driven environment.
• Must not have had any disciplinary actions regarding attendance, conduct and/or performance in the past 90 days, and must not be approaching such action.

DESIRED SKILLS

• Experience using: Excel, Google Sheets, Slack
• AWS cloud practitioner or engineer certificates are a plus
• High speed Wi‑Fi connection
• Be able to work in US timezone shifts (e.g., EST, CST, MST, or PST).