Data Engineer - Data Engineering (CD - DE - 20261006)

MotoTech, Inc.; Buenos Aires; Hybrid; ARS 1,800,000 - 3,000,000; Full time

Benefits offered by this job

Competitive Compensation

Professional Growth

Great Culture

Job summary

Celara is seeking a Data Engineer in Buenos Aires with strong SQL and Python skills to design, build, and maintain scalable data pipelines and data models. You will work with engineers, analysts, and data scientists to deliver reliable data for analytics, AI, and reporting, while ensuring governance and quality.

The role emphasizes hands-on engineering, collaboration, and maintaining high data standards in a remote-friendly environment.

Qualifications

• Bachelor’s degree in CS/IS/Engineering or related field, or equivalent experience.
• Advanced SQL with complex joins, CTEs, window functions, and tuning.
• Experience building ETL/ELT pipelines for high-volume data.

Responsibilities

• Design, build, and maintain scalable data pipelines ingesting data from multiple sources.
• Develop and maintain data models, data warehouse, and lakehouse structures.
• Write clean, well-documented SQL and Python code.
• Implement data quality checks, validation, and monitoring to ensure data accuracy.
• Optimize pipeline and query performance for large datasets.
• Participate in code reviews and uphold data engineering standards.
• Collaborate with product managers, analysts, data scientists, and engineers.
• Troubleshoot pipeline failures with Data Operations.
• Support data security and governance practices.
• Stay updated on new data tech and AI tooling.

Skills

Advanced SQL

Python (pandas)

ETL/ELT pipelines

Data modeling

Airflow

Docker

Kubernetes

CI/CD

Azure

Education

Bachelor’s degree in CS/IS/Engineering

Tools

Airflow

Docker

Kubernetes

Git

Job description

# Data Engineer - Data Engineering (CD - DE - 20261006)CelaraBuenos AiresRemoteFull Time## DescriptionIn this role, the Data Engineer will join the Data Engineering team. You'll design, build, and maintain the data pipelines and data models that power the company's freight and parcel audit, analytics, and AI solutions.You'll work with software engineers, analysts, data scientists, and business teams to deliver reliable, scalable, and well-governed data. The business focuses on logistics contract negotiation, optimization, and audit.The ideal candidate is a data engineer with strong SQL and Python skills who has built pipelines and data models for large, high-volume datasets and cares about data quality and governance.Most of this role is hands-on engineering, with steady collaboration with technical and business teams.What You'll Do* Design, build, and maintain scalable data pipelines that ingest, transform, and load data from carriers, clients, and internal systems.* Develop and maintain data models, data warehouse, and data lake structures that support reporting, analytics, and AI initiatives.* Write clean, efficient, well-documented SQL and Python code.* Implement data quality checks, validation, and monitoring to keep data accurate and reliable.* Optimize pipeline and query performance for large, high-volume datasets.* Take part in code reviews and contribute to team best practices and data engineering standards.* Work with product managers, internal customers, analysts, data scientists, and software engineers to define and deliver data solutions.* Troubleshoot and fix pipeline failures and data issues, working with Data Operations on root cause and prevention.* Support data security, access control, and governance practices.* Keep up with new data technologies and industry trends, including AI tools that make engineering more productive.## RequirementsRequired* Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent experience).* Advanced SQL experience, including complex joins, CTEs, window functions, and performance tuning.* Databases: MSSQL and PostgreSQL* Languages: Python (pandas)* Experience designing and building ETL/ELT pipelines for high-volume data.* Experience with workflow orchestration and integration tools (e.g., Airflow)* Understanding of data modeling concepts (dimensional modeling, normalization, data warehouse and lakehouse design) and performance/optimization implications* Knowledge of containerization tools (e.g., Docker, Kubernetes)* Experience with cloud data platforms (Azure preferred; e.g., Azure Data Lake, Synapse).* Familiarity with CI/CD pipelines, Git, and DevOps practices.Preferred* Pyspark knowledge is a plus* Experience with Azure ML Studio,* Experience with freight, parcel, invoice, or other transactional data is a plus.## Benefits* Competitive Compensation: Market-aligned salary package.* Professional Growth: Direct impact on product architecture and tech leadership.* Great Culture: Collaborative, low-friction, and high-performing environment.