Senior Data Engineer Lead

Join EVA Pharma, a leading pharmaceutical company dedicated to empowering the fight for Health and well-being as a fundamental human right. Recognized and certified as a best place to work, we are committed to fostering a supportive and innovative environment for our team members. Job Summary: We are seeking a passionate and talented Data Engineer Senior Lead to join our dynamic team. The ideal candidate will contribute to our mission of enhancing human health and well-being, ensuring that we meet the highest standards of excellence in our industry. Key Responsibilities: Design, develop, and maintain reliable ETL/ELT pipelines that move data from multiple sources into cloud-based warehouses such as Snowflake, BigQuery, or Databricks. Ensure real-time or near–real-time data processing for analytics dashboards and operational systems. Continuously fine-tune performance to handle growing data volumes efficiently. Implement automated validation checks, anomaly detection, and alerting systems to maintain high data accuracy. Ensure all pipelines comply with data privacy and security standards (e.g., GDPR, SOC 2). Maintain clear documentation and data lineage to support audits and cross-team visibility. Evaluate and introduce new tools like Airflow, dbt, Kafka, or Spark to improve efficiency and scalability. Collaborate with AI/ML teams to enable deployment and integration of advanced models. Develop best practices for data modeling, storage optimization, and version control. Align data structures with key business metrics and analytics use cases to ensure consistency across departments. Conduct design reviews, ensure high-quality code, and promote a collaborative culture focused on innovation and continuous improvement. Also, Mentor and coach data engineers to enhance their technical skills and improve project execution. Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field. 7-10 years of experience in data engineering or related fields, with at least 2 years in a leadership role. Proven ability to design, build, and optimize scalable ETL/ELT pipelines and data workflows for analytics and operational use. Strong skills in SQL and Python, with hands-on experience in cloud-based data platforms and distributed systems. Deep understanding of data modeling, data warehousing, orchestration tools (e.g., Airflow, Prefect), and big data technologies such as Spark and Databricks. Solid grasp of data governance, privacy, and security best practices, combined with strong problem-solving, architectural design, and cross-functional collaboration abilities.