Senior Engineer, Data Engineering

Our global team of more than 7,000 employees is committed to creating and delivering next-generation commercialization services to the life sciences industry. We are grounded in our cultural beliefs and serve more than 650 clients ranging from innovative biotech start-ups to established pharmaceutical companies. Our products, services and solutions help bring innovative therapies to market and support the patients who depend on them. Our jobs, skills and talents are unique, but together we make an impact every day. Across our growing organization, we embrace diversity in backgrounds and experiences. Improving patient lives around the world is a priority, and we need people from all backgrounds and swaths of life to help build the future of the healthcare and the life sciences industry. We are deliberate and self-reflective about the kind of team and culture we are building. Senior Associate, reporting to Associate Director - Engineering, will play an essential role in designing, developing, and maintaining scalable data pipelines and data infrastructure. You will work closely with data scientists, analysts, and other stakeholders to ensure that our data systems are efficient, reliable, and capable of supporting complex analytical queries. Your role will involve a mix of hands-on technical work and strategic planning to support the organization's data needs. To be successful as a Senior Data Engineer at Eversana, you should have strong analytical skills and the ability to combine data from different sources. Data engineer skills include familiarity with several programming languages and learning machine methods. Design, build, and maintain scalable data pipelines that facilitate the flow of data into machine learning models. • Collaborate with data scientists to ensure the availability of high-quality, preprocessed data for model training. • Deploy machine learning models to production using tools such as TensorFlow Serving, MLflow, or Seldon. • Monitor and maintain the performance of machine learning models in production, identifying and addressing issues like data drift or concept drift. • Work with large datasets, both batch and real-time, using frameworks like Apache Spark, Apache Kafka, and AWS Glue. • Implement and manage data versioning and experiment tracking using tools like DVC and MLflow. • Ensure data integrity and quality through validation and profiling techniques Proficiency in Python and SQL; experience with Scala or Java is a plus. • Strong experience with Apache Spark, Apache Kafka, and other data processing frameworks. • Experience deploying machine learning models using TensorFlow Serving, MLflow, or similar tools. • Familiarity with data lakes and data warehouses (AWS S3, Google BigQuery, Snowflake). • Experience with cloud platforms (AWS, GCP, Azure) and containerization tools like Docker and Kubernetes. • Understanding of machine learning workflows and collaboration with data scientists and ML engineers. • Strong knowledge of ETL processes, batch and real-time data processing, and orchestration tools (e.g., Bachelor’s degree in engineering, Technology, or Computer Science • 1+ years of relevant industry experience (Healthcare, Pharmaceutical Consulting, Enterprise level data-analytical solutio Client Delight I own every client experience and its impact on results. Grow Talent I own my development and invest in the development of others.  Embrace Diversity I create an environment of awareness and respect. Always Innovate  I am bold and creative in everything I do.   Recruitment fraud is a sophisticated scam commonly perpetrated through online services using fake websites, unsolicited e-mails, or even text messages claiming to be a legitimate company. Some of these scams request personal information and even