Lead Data Engineer (Azure)

AIDA Recruitment · Argentina · posted today ago

Listing supplied by Himalayas. 101 Careers did not originate this post and applications are handled by the employer.

About this role

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
Guide the Data Engineering team on technical decisions, engineering practices, troubleshooting, and successful solution deliveryTeam DescriptionIn 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.