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Syneos Health
Principal Data Engineer- Hyderabad (Hybrid)
Syneos Health
Hyderabad•Hybrid•8-11 Yrs•Jun 30
Job description
Hybrid
Overview
Principal Data Engineer- Hyderabad (Hybrid)
Responsibilities
- We are passionate about developing our people, through career development and progression; supportive and engaged line management; technical and therapeutic area training; peer recognition and total rewards program.
- We are committed to building an inclusive culture – where you can authentically be yourself. Central to this is our purpose – Driven to Deliver – which captures the passion of our colleagues to show up each day and shape solutions that have the ability to dramatically impact someone’s life.
- We are continuously building the company we all want to work for and our customers want to work with. Why? Because we know that when we bring together smart colleagues from across the world, we can shape the future of healthcare, driving impact for customers and defining the pace of patient progress.
- Job Summary
- Demonstrate extensive hands-on experience with Azure Databricks, Apache Spark, Azure Data Factory (ADF), using these technologies to build, optimize, and scale enterprise data solutions.
- Exhibit deep expertise in designing and implementing robust ingestion logic, frameworks, and pipelines across diverse source systems, using ADF, Databricks, and related tools to ensure seamless data flow and integration.
- Lead the design and strategic planning of enterprise-wide data platforms, ensuring alignment with business objectives, scalability, and future-proofing against emerging trends.
- Direct the development, optimization, and governance of advanced data pipelines and frameworks, supporting high-volume, high-velocity, and high-variety data streams for analytics, machine learning, and operational workloads.
- Collaborate with executive leadership, product managers, and cross-functional teams to define data engineering roadmaps, drive major digital transformation initiatives, and ensure successful integration of data-driven solutions into production environments.
- Establish and enforce best practices and standards for data architecture, quality, security, and compliance, including data governance, data lineage, and privacy regulations.
- Oversee the creation and maintenance of comprehensive documentation for data models, storage solutions, and data pipelines, ensuring knowledge transfer and operational excellence.
- Mentor and coach data engineers, fostering a culture of high performance, technical excellence, and continuous professional growth within the data engineering organization.
- Evaluate, recommend, and drive adoption of cutting-edge technologies, frameworks, and methodologies in the data engineering landscape, including cloud-native solutions, real-time data processing, and automation.
- Lead advanced research and prototyping efforts to identify innovative opportunities for using data assets, improving operational efficiency, and strengthening the company’s data-driven decision-making capabilities.
Qualifications
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a closely related field.
- Minimum of ten (10) years of progressive experience in data engineering, with a proven track record of leading large-scale data platform solutions and architectural initiatives.
- Demonstrated expertise in designing, building, and optimizing ETL/ELT pipelines using ADF, Databricks, and modern cloud-native architectures.
- Mastery of data modeling, relational database systems, and architecting APIs for data access and integration at scale.
- Advanced proficiency in Python, SQL, and other programming languages commonly used in data engineering; experience with Spark, Scala is highly desirable.
- Deep experience with distributed version control systems (e.g., Git) and managing collaborative development workflows across large engineering teams.
- Strong analytical, problem-solving, and data processing skills, with a demonstrated ability to architect resilient, efficient, and secure data solutions.
- Proven leadership ability to drive complex projects from conception to delivery, manage priorities, and deliver impactful results for the business.
- Exceptional communication skills, with an ability to articulate complex technical concepts and strategies to both technical and non-technical audiences, including executive stakeholders.
Nice to have
- 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.
- In-depth knowledge of data masking, data governance, and security best practices within Databricks and other cloud data platforms.
- Hands-on experience with AI/ML integration, advanced analytics, and leveraging AI functions in Databricks or comparable platforms.
- Familiarity with industry-specific data standards (e.g., clinical trial data, healthcare, financial services) and regulatory compliance frameworks.
- Recognized advanced certifications in cloud data engineering (e.g., Microsoft Certified: Azure Data Engineer Expert), data architecture, or related domains.