Data Engineer II leading development and delivery of data pipelines for Syneos Health. Collaborating with teams to optimize data processing and integrate solutions into production environments.
About the role
- Data Engineer I developing data services with Azure technology for global risk management insights. Collaborating with teams to optimize data processes and ensure quality standards.
Responsibilities
- Design and implement data pipelines to efficiently extract, transform, and load (ETL) data from various sources into a central data lake using Azure Data Factory and Azure Databricks
- Transform and process data using Python, PySpark, and SQL to create valuable insights
- Collaborate with peers and senior team members to optimize data processes and solve complex challenges
- Ensure data quality by performing thorough checks and troubleshooting issues
- Apply best practices in data engineering for reliability and performance
- Optimize pipelines for maximum efficiency and cost-effectiveness
- Document comprehensively and maintain data mapping across multiple systems
- Provide hands-on troubleshooting and consulting for data challenges when needed
- Perform basic unit testing to maintain data quality standards
Requirements
- Bachelor's or master's degree in computer science, information technology, or a related field
- Approximately 2-3 years of experience in a data-related role, preferably data engineering
- Hands-on expertise with programming languages such as Python, PySpark, and SQL
- Working knowledge of data processing frameworks or ETL tools like Azure Data Factory and Azure Databricks
- Experience with Azure DevOps or similar CI/CD tools
- Experience in agile software engineering methodologies (nice to have)
- Strong analytical and problem-solving skills to tackle complex data challenges (nice to have)
- Excellent interpersonal and communication skills, both written and verbal (nice to have)
- Meticulous attention to detail and commitment to data accuracy (nice to have)
- Knowledge of AI tools like CoPilot, ChatGPT, etc. (nice to have)
- Eagerness to learn and collaborate with team members (nice to have)
Benefits
- hybrid work model where expectation is to be in office at least three days per week
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