Lead Data Engineer (Azure)
Senior/lead data engineer role designing and optimizing scalable ETL and data integration pipelines on Azure (Data Factory, Synapse) using SQL, Python, Spark/PySpark, and Airflow, while guiding the data engineering team and collaborating with international clients. Remote position based in Brazil or Argentina.
- Compensation
- Not disclosed
- Location
- Buenos Aires, Argentina
- Work setup
- Remote
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 5+ years of experience in Data Engineering, incl. hands-on ETL pipeline and data integration development
- 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 orchestration and scheduling
- Strong understanding of Data Architecture, Data Modeling, Data Quality, Data Integration, and SQL/ETL performance optimization
- Proven ability to provide technical guidance to engineering teams and serve as a technical reference
- Strong working proficiency in English for communication with international clients and teams
- Client-facing, communication, analytical, and problem-solving skills
Nice to have
- Exposure to Microsoft Fabric, Hadoop, Hive, Kafka, Power BI, or Tableau
- Experience with healthcare or pharmaceutical data environments
Full 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
- 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