Senior Data Engineer Pharma

Job Description:

The Senior Data Engineer will be responsible for designing developing and maintaining scalable cloud-based data platforms and data pipelines. The role requires strong expertise in AWS Snowflake Databricks Python SQL and PySpark along with experience in batch and real-time data processing. The candidate will collaborate with cross-functional teams to build reliable secure and high-performance data solutions that support analytics reporting and AI/ML initiatives.

Key Responsibilities:

• Design develop and maintain scalable data pipelines and ETL/ELT frameworks.
• Build and optimize batch and real-time streaming solutions using PySpark and cloud-native services.
• Develop and manage enterprise data platforms using AWS Snowflake and Databricks.
• Design and implement robust data models data lakes data warehouses and lakehouse architectures.
• Integrate data from multiple sources while ensuring data quality governance and security.
• Optimize performance and scalability of data processing workloads.
• Collaborate with Data Scientists Analysts Architects and business stakeholders to deliver data solutions.
• Implement monitoring alerting and automated data validation processes.
• Contribute to architecture reviews technical documentation and best practices.
• Mentor junior engineers and participate in code reviews.
• Stay updated on emerging cloud and data engineering technologies.

Required Skills and Experience:

• 5-8 years of relevant experience in Data Engineering Big Data and Cloud Data Platform development.
• Strong proficiency in Python SQL and PySpark.
• Hands-on experience designing developing and maintaining scalable data platforms on AWS Cloud.
• Strong expertise in Snowflake and Databricks for enterprise-scale data engineering solutions.
• Experience building and optimizing batch and real-time streaming data pipelines.
• Strong understanding of Data Modeling concepts including Dimensional Modeling Star Schema Snowflake Schema and Data Vault.
• Experience designing and implementing ETL/ELT pipelines for large-scale enterprise data platforms.
• Strong expertise in Apache Spark and distributed data processing frameworks.
• Experience building and managing Data Lakes Data Warehouses and Lakehouse architectures.
• Hands-on experience with AWS services such as S3 Glue EMR Lambda Redshift Athena EC2 ECS/EKS Kinesis MSK Step Functions CloudWatch IAM RDS DynamoDB EventBridge SNS and SQS.
• Experience integrating data from multiple structured and unstructured data sources.
• Strong understanding of data governance security data quality and performance optimization best practices.
• Experience with version control systems such as Git and collaborative development workflows.
• Proficiency with CI/CD pipelines and software engineering best practices.
• Strong problem-solving skills with the ability to debug troubleshoot and resolve complex data engineering challenges.
• Ability to design scalable and maintainable data solutions using modern architectural patterns and best practices.
• Proven ability to work collaboratively in cross-functional teams including participation in code reviews technical discussions and knowledge-sharing initiatives.
• Experience working in Agile/Scrum delivery environments.
• Strong communication skills and ability to interact with business and technical stakeholders.
• Experience in Healthcare Pharma or Real-World Evidence (RWE) data environments (good to have).
• Experience with Infrastructure as Code (Terraform/CloudFormation) (good to have).
• Experience with Docker and Kubernetes (good to have).
• Knowledge of Data Mesh CDC and Event-Driven Architectures (good to have).
• Exposure to MLOps and AI/ML platform integration (good to have).
• AWS Snowflake or Databricks certifications (good to have).

Being a Mathemagician:

• Embody MathCos culture and way of working.
• Demonstrate ownership and strive for excellence in delivering results.
• Actively engage and contribute to initiatives fostering company growth.
• Support diversity and appreciate different perspectives.

Required Experience:

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