Lead Data Engineer (Azure)

AIDA projektai, MB; Buenos Aires; On-site; ARS 138,361,000 - 199,855,000; Full time

Job summary

AIDA projektai, MB is seeking a Senior Data Engineer / Technical Lead to architect and deliver scalable data solutions in Azure environments. You will own end-to-end data pipelines, collaborate with international clients, and provide technical leadership to the engineering team.

The ideal candidate has 5+ years in data engineering, strong SQL/Python skills, Spark/PySpark experience, and hands-on Azure Data Factory/Synapse expertise. English communication is essential for global projects.

Qualifications

• 5+ years of experience in Data Engineering, including ETL pipelines and data integration.
• Advanced proficiency in SQL and Python for data processing and transformations.
• Strong experience with Spark/PySpark for distributed data processing.
• Hands-on with Azure data technologies and cloud-based data platforms.
• Experience with Azure Synapse, Azure Data Factory and Apache Airflow for orchestration.

Responsibilities

• Design and develop scalable ETL and data integration pipelines across Azure data environments.
• Own technical implementation and solution quality, ensuring reliable data processing.
• Collaborate with clients, Solution Architects, and engineering teams to translate requirements into data solutions.
• Build and optimize data processing workflows using SQL, Python, Spark, PySpark, Azure Data Factory, and Airflow.
• Develop data models and schemas aligned with business and downstream needs.
• Implement data quality and validation controls to maintain data integrity.
• Optimize queries and ETL processes to improve performance.
• Guide the Data Engineering team on technical decisions and best practices.

Skills

SQL

Python

Spark/PySpark

Data architecture

Data modeling

English communication

Tools

Azure Data Factory

Azure Synapse

Apache Airflow

Azure cloud

Job description

We are looking for a Senior Data Engineer / Technical Lead with 5+ years of experience and strong hands-on expertise in SQL, Python, Spark/PySpark, and Azure (Azure Data Factory, Synapse, Apache Airflow).

The ideal candidate should have solid experience in ETL pipeline development, data integration, and data modeling, as well as the ability to provide technical guidance to engineering teams and communicate effectively with international clients in English.

Location: Brazil or Argentina.

REQUIREMENTS:

• 5+ years of experience in Data Engineering, including hands-on development of ETL pipelines and data integration solutions
• Advanced proficiency in SQL and Python for data processing, transformation, and optimization
• Strong experience with Spark and PySpark for distributed data processing
• Hands-on experience with Azure data technologies and cloud-based data platforms
• Advanced proficiency with Azure Synapse, Azure Data Factory and/or Apache Airflow for workflow orchestration and scheduling
• Strong understanding of Data Architecture, Data Modeling, Data Quality, Data Integration, and SQL and ETL performance optimization
• Proven ability to provide technical guidance to engineering teams and serve as a technical reference throughout project delivery
• Strong working proficiency in English for daily communication with international clients and teams
• Client-facing, communication, analytical, and problem-solving skills
• Exposure to Microsoft Fabric, Hadoop, Hive, Kafka, Power BI, or Tableau as a plus
• Experience with healthcare or pharmaceutical data environments as an advantageSelling PointsRESPONSIBILITIES

RESPONSIBILITIES

• Design and develop scalable ETL and data integration pipelines across Azure data environments
• Own technical implementation and solution quality, ensuring reliable, scalable, and maintainable data processing
• Collaborate with clients, Solution Architects, and engineering teams to translate business requirements into effective data solutions
• Build and optimize data processing workflows using SQL, Python, Spark, PySpark, Azure Data Factory, and Apache Airflow
• Develop data models and schemas aligned with business requirements, architecture standards, and downstream consumption needs
• Implement data quality and validation controls to maintain data integrity and consistency across platforms
• Optimize SQL queries, ETL processes, and data workflows to improve performance and reliability
• Guide the Data Engineering team on technical decisions, engineering practices, troubleshooting, and successful solution delivery

Team Description

In this role, you will design and deliver scalable data solutions within Azure environments while serving as a technical reference for the engineering team. Combining hands‑on Data Engineering with technical leadership, you will work closely with clients and architects to translate business needs into reliable solutions across the delivery lifecycle, with a focus on data integration, performance, and quality.

Interview Process

Approximately 2–3 stages, including a short AI‑led Q&A session focused on the candidate's experience, an interview with the project team, and a final interview with the end client.