Principal Data Engineer

As a Principal Data Engineer at Syneos Health, you will be a senior technical leader responsible for setting the strategic direction and architectural vision of the enterprise data engineering initiatives. Your key responsibilities will include: - Demonstrating extensive hands-on experience with Azure Databricks, Apache Spark, Azure Data Factory (ADF) to build, optimize, and scale enterprise data solutions. - Exhibiting deep expertise in designing and implementing robust ingestion logic, frameworks, and pipelines across diverse source systems to ensure seamless data flow and integration. - Leading the design and strategic planning of enterprise-wide data platforms, ensuring alignment with business objectives and future-proofing against emerging trends. - Directing the development, optimization, and governance of advanced data pipelines and frameworks to support high-volume, high-velocity, and high-variety data streams for analytics and machine learning. - Collaborating with executive leadership and cross-functional teams to define data engineering roadmaps, drive digital transformation initiatives, and ensure successful integration of data-driven solutions into production environments. - Establishing and enforcing best practices and standards for data architecture, quality, security, and compliance, including data governance and privacy regulations. - Overseeing the creation and maintenance of comprehensive documentation for data models, storage solutions, and data pipelines to ensure operational excellence. - Mentoring and coaching data engineers to foster a culture of high performance, technical excellence, and continuous professional growth within the data engineering organization. - Evaluating, recommending, and driving the adoption of cutting-edge technologies, frameworks, and methodologies in the data engineering landscape. Qualification Requirements: - Bachelor's degree in Computer Science, Engineering, Mathematics, or a closely related field. - Minimum of ten years of progressive experience in data engineering, with expertise in designing, building, and optimizing ETL/ELT pipelines using ADF, Databricks, and modern cloud-native architectures. - Proficiency in Python, SQL, and other programming languages commonly used in data engineering, with experience in Spark and Scala highly desirable. - Strong leadership skills with the ability to drive complex projects from conception to delivery and deliver impactful results for the business. - Exceptional communication skills to articulate complex technical concepts and strategies to both technical and non-technical audiences. Preferred Qualifications: - Master's degree in Computer Science, Engineering, Mathematics, or a closely related field. - Advanced expertise in CI/CD automation, DevOps practices, and infrastructure-as-code for data engineering solutions. - Proficiency in Spark, Databricks, ADF, and advanced distributed data processing frameworks. - Hands-on experience with AI/ML integration, advanced analytics, and leveraging AI functions in Databricks or comparable platforms. - Knowledge of industry-specific data standards and regulatory compliance frameworks. As a Principal Data Engineer at Syneos Health, you will play a crucial role in driving innovation and shaping the future of healthcare through data-driven decision-making capabilities. As a Principal Data Engineer at Syneos Health, you will be a senior technical leader responsible for setting the strategic direction and architectural vision of the enterprise data engineering initiatives. Your key responsibilities will include: - Demonstrating extensive hands-on experience with Azure Databricks, Apache Spark, Azure Data Factory (ADF) to build, optimize, and scale enterprise data solutions. - Exhibiting deep expertise in designing and implementing robust ingestion logic, frameworks, and pipelines across diverse source systems to ensure seamless data flow and integration. - Leading the design and strategic planning of enterprise-wide data platforms, ensuring alignment with business objectives and future-proofing against emerging trends. - Directing the development, optimization, and governance of advanced data pipelines and frameworks to support high-volume, high-velocity, and high-variety data streams for analytics and machine learning. - Collaborating with executive leadership and cross-functional teams to define data engineering roadmaps, drive digital transformation initiatives, and ensure successful integration of data-driven solutions into production environments. - Establishing and enforcing best practices and standards for data architecture, quality, security, and compliance, including data governance and privacy regulations. - Overseeing the creation and maintenance of comprehensive documentation for data models, storage solutions, and data pipelines to ensure operational excellence. - Mentoring and coaching data engineers to foster a culture of high performance, technical excellence,