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Parexel is seeking a highly experienced Senior Data Engineer to architect, develop, and optimize enterprise-grade data pipelines and platforms using Azure, Databricks, Snowflake and Power BI. This role is pivotal in transforming raw data into actionable insights and building a resilient, scalable data ecosystem that supports business-critical functions across clinical and operational domains.
Key Responsibilities:
1. Architect and implement end-to-end data pipelines using Azure Data Factory, Databricks, and Snowflake for large-scale data ingestion, transformation, and storage.
2. Using Microsoft Azure data PaaS services, design, build, modify, and support data pipelines leveraging DataBricks and PowerBI in a medallion architecture setting
3. If necessary, create prototypes to validate proposed ideas and solicit input from stakeholders
4. Excellent grasp of and expertise with test-driven development and continuous integration processes
5. Analysis and Design – Converts high-level design to low-level design and implements it
6. Collaborate with Team Leads to define/clarify business requirements, estimate development costs, and finalize work plans
7. Run unit and integration tests on all created code – Create and run unit and integration tests throughout the development lifecycle
8. Benchmark application code proactively to prevent performance and scalability concerns
9. Collaborate with the Quality Assurance Team on issue reporting, resolution, and change management
10. Support and Troubleshooting – Assist the Operations Team with any environmental issues that arise during application deployment in the Development, QA, Staging, and Production environments
11. Familiarity with PowerBI and Reltio is advantageous but not required
12. Collaborate with BI teams to ensure data models are optimized for reporting in Power BI, with a focus on performance and usability.
13. Establish data governance, quality, and security controls, ensuring compliance with GDPR, HIPAA, and global clinical data regulations.
14. Mentor and guide junior engineers, fostering technical excellence and knowledge sharing.
15. Drive automation and CI/CD practices within data engineering pipelines, integrating with version control and deployment workflows.
16. Work closely with Data Architects, Business Analysts, and Product Owners to translate business needs into technical solutions.
Required Qualifications:
17. Experience: 6+ years of data engineering experience, with at least 4 years hands-on in Azure, Databricks, and Snowflake; experience with Reltio and Power BI integration is highly desirable.
18. Education: Bachelor’s or master’s degree in computer science, Information Systems, Engineering, or a related field.
Skills:
19. Expert-level knowledge of Azure Data Factory, Databricks, and Snowflake.
20. Understanding of quality processes and estimate methods
21. Understanding of design concepts and architectural basics
22. Fundamental grasp of the project domain
23. The ability to transform functional and nonfunctional needs into system requirements.
24. The ability to develop and code complicated applications is required.
25. The ability to create test cases and scenarios based on specifications.
26. Solid knowledge of SDLC and agile techniques
27. Knowledge of current technology and trends
28. Logical thinking and problem-solving abilities, as well as the capacity to collaborate
29. Primary skills: Cloud Platform, Azure, Databricks, ADF, ADO
30. Advantageous: SQL, Python, PowerBI
31. General Knowledge: PowerApps, Java/Spark, Reltio
32. 3-5 years of experience in software development with minimum 2 years of cloud computing
33. Proven experience in building BI-ready datasets and performance tuning in Power BI
34. Proficient in SQL, Python, and cloud-native architecture.
35. Strong grasp of data security, privacy compliance, and best practices in a regulated environment.