Lead Data Engineer (Azure)

ABOUT THE ROLE

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.

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

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 advantage