Data Engineer (Senior) – BI & Data Analytics (Argentina or Uruguay)

RemoteLeads; Argentina; Hybrid; ARS 136,310,000 - 212,038,000; Full time

Benefits offered by this job

Hybrid/Remote work options

International projects

Continuous learning

Multicultural teams

Healthy work-life balance

Competitive compensation

Job summary

RemoteLeads is seeking an experienced Data Engineer to design and deliver end-to-end data solutions for enterprise clients. You will translate business requirements into scalable architectures, build data lakes and warehouses, and develop robust data pipelines.

You will mentor teammates and lead technical delivery for international projects. You should have 3+ years of data engineering experience, strong SQL and PySpark skills, cloud platform experience (Azure/AWS/GCP), and excellent English

Qualifications

• 3+ years as Data Engineer / Analytics Engineer / BI Developer or similar role
• Strong SQL, PySpark and data modeling experience
• Hands-on with cloud data platforms on Azure, AWS, or GCP
• Experience designing and building production-grade data solutions
• Advanced English (spoken & written) and client-facing communication
• Demonstrated technical leadership without formal people management
• Ownership, autonomy and problem-solving mindset
• Experience with Fabric, lakehouse architectures, notebooks, Power BI, Synapse or dataflows is a plus
• Experience with Databricks, Snowflake or Parquet and modern columnar storage formats is a plus

Responsibilities

• Design and deliver end-to-end data solutions for enterprise clients
• Gather requirements and translate into scalable architectures
• Build and maintain Data Lake, Data Warehouse and analytical models
• Develop data pipelines for ingestion, transformation and serving
• Ensure technical quality via best practices, docs, testing and version control
• Serve as technical point of contact for clients during delivery
• Mentor and support other Data Engineers
• Participate in estimations, design and project planning
• Continuous improvement of engineering standards and delivery processes

Skills

SQL

PySpark

Data modeling

Job description

Description:

• Design and deliver end-to-end data solutions for enterprise clients.
• Gather business requirements and translate them into scalable technical architectures.
• Build and maintain Data Lake, Data Warehouse, and analytical data models.
• Develop data pipelines for ingestion, transformation, and data serving.
• Drive technical quality through best practices, documentation, testing, and version control.
• Act as the technical point of contact for clients during project delivery.
• Mentor and support other Data Engineers.
• Participate in technical estimations, solution design, and project planning.
• Continuously improve engineering standards and delivery processes.

Requirements:

• 3+ years of experience as a Data Engineer, Analytics Engineer, BI Developer, or a similar role.
• Strong experience with SQL, PySpark, and data modeling.
• Hands-on experience implementing cloud-based data platforms on Azure, AWS, or GCP.
• Experience designing and building production-grade data solutions.
• Advanced English, both spoken and written.
• Comfortable working directly with clients and multiple stakeholders.
• Demonstrated technical leadership without formal people management responsibilities.
• Strong ownership, autonomy, and problem-solving mindset.
• Experience with Microsoft Fabric, lakehouse architecture, notebooks, Power BI, Synapse, or dataflows is a plus.
• Experience with Databricks, Snowflake, or Parquet and modern columnar storage formats is a plus.

Benefits:

• Full-time schedule, Monday to Friday.
• Hybrid work model from Uruguay or fully remote from Argentina.
• Opportunity to work on enterprise-scale data platforms.
• International projects with global clients.
• Collaborative engineering culture with strong technical ownership.
• Continuous learning, certifications, and professional development.
• Multicultural teams.
• Healthy work-life balance.
• Competitive compensation and benefits.