Data Engineer

VeroSource Solutions is seeking an experienced Data Engineer to join our innovative team and help drive the success of our Data Team's projects and products such as VS Data-as-a-Service (DaaS) and VS Digital Twin. These solutions are central to how we deliver actionable insights, interoperability, and secure digital health ecosystems for our clients, and are core components of the VS Platform.

As a Data Engineer at VeroSource, you will design, build, and optimize scalable data pipelines and architectures across Azure and AWS platforms, contributing directly to the evolution, reliability, and scalability of the VS Platform's data capabilities. In this role, you will also work with client Subject Matter Experts (SMEs) to understand business needs and translate them into data solutions that directly support improved decision-making and operational outcomes.

• Design, implement, and maintain robust ETL/ELT pipelines to support our Data Team's solutions.
  
• Optimize data lakehouses for performance, scalability, and secure access.
  
• Collaborate with internal teams and client SMEs to gather requirements, define data models, and deliver tailored data solutions.
  
• Develop and maintain APIs and interfaces to facilitate secure and seamless data exchange across systems.
  
• Ensure data quality, integrity, and compliance with regulatory standards, particularly in healthcare and digital health contexts.
  
• Participate in agile ceremonies, including sprint planning, stand-ups, and retrospectives, to align technical work with client and product priorities.
  
• Provide technical guidance and best practices to both internal teams and client stakeholders.
  
• Explore and evaluate emerging technologies to enhance data engineering practices and platform capabilities.
  
• Provide support to quickly resolve production issues when they arise.
  

• Bachelor's degree in Computer Science, Engineering, or related field.
  
• 5 years of experience in data engineering or a related role.
  
• Ability to take vague or partially defined requirements and, with minimal direction, develop a clear plan and implement an effective solution.
  
• Proven experience with either/both Azure Data Services (e.g., Data Lake, Databricks, Synapse, Data Factory) and AWS Data Services (e.g., EC2, Glue, S3, Athena).
  
• Strong skills in Python, SQL, and PySpark. Experience in other programming languages such as Java is also helpful.
  
• Experience designing and managing data models and architectures for analytical and operational solutions.
  
• Ability to work effectively with client SMEs to gather requirements, analyze data workflows, and co-create solutions.
  
• Familiarity with distributed systems, big data architectures, and pipeline orchestration tools.
  
• Experience with CI/CD pipelines and version control systems such as Gitlab.
  
• Excellent communication and collaboration skills, with the ability to translate technical concepts for non-technical audiences.
  

• Experience with real-time data streaming tools such as Kafka or Kinesis.
  
• Familiarity with data governance platforms and cataloging tools.
  
• Exposure to containerization and orchestration technologies like Docker and Kubernetes.
  
• Interest in AI-driven data engineering and analytics to support predictive modeling.
  
• Knowledge of healthcare data exchange standards (e.g., HL7, FHIR) and regulatory compliance requirements.