Lead Data Engineer (Azure)

• 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

• 5+ years of experience in Data Engineering, including hands-on development of ETL pipelines and data integration solutions

• +2 years of experience as Data Engineer Lead

• 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