Senior Data Engineer & Tech Lead - Azure, Spark, ETL

AIDA Recruitment; Buenos Aires; On-site; ARS 138,564,000 - 200,148,000; Full time

Job summary

A Senior Data Engineer/Technical Lead role at AIDA Recruitment focuses on leading data engineering efforts to design and deliver scalable ETL pipelines in Azure-centric environments. You will translate complex business requirements into robust data solutions while guiding engineering teams and communicating with international clients in English.

You will own data models, workflow orchestration with Airflow, and performance optimization across Spark/PySpark pipelines, ensuring high data quality

Qualifications

• 5+ years of experience in Data Engineering, including ETL pipelines and data integration.
• Advanced proficiency in SQL for data processing and optimization.
• Strong experience with Spark/PySpark for distributed data processing.
• Hands-on experience with Azure data technologies and cloud platforms.
• Experience with data modeling and data quality controls.

Responsibilities

• Design and develop scalable ETL and data integration pipelines across Azure environments.
• Own technical implementation and ensure reliable, scalable data processing.
• Collaborate with clients, 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 aligned with business needs and downstream consumption.
• Implement data quality and validation controls to maintain data integrity.

Skills

SQL

Python

Data modeling

ETL development

Data integration

Data architecture

Data quality

English communication

Tools

Spark/PySpark

Azure Data Factory

Azure Synapse

Apache Airflow

Job description

A Senior Data Engineer/Technical Lead role at AIDA Recruitment focuses on leading data engineering efforts to design and deliver scalable ETL pipelines in Azure-centric environments. You will translate complex business requirements into robust data solutions while guiding engineering teams and communicating with international clients in English.

You will own data models, workflow orchestration with Airflow, and performance optimization across Spark/PySpark pipelines, ensuring high data quality