Description

Principal Data Engineer- Hyderabad (Hybrid)

Syneos Health® is a leading fully-integrated life sciences services organization built to accelerate customer success. We partner with innovators at every point across the drug development and commercialization continuum, helping them navigate complexity, anticipate change and accelerate progress.

Every day we perform better because of how we work together, as one team, each the best at what we do. We bring together talented experts across a broad spectrum of business critical corporate functions. Every role plays an essential part in enabling our customers to achieve their goals. Our teams are agile, collaborative, and committed to delivering—for each other, for our customers, and ultimately for the people who rely on the services we support.

Discover what your 25,000 future colleagues already know:

Why Syneos Health

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 Responsibilities

Job Summary

The Principal Data Engineer is a senior technical leader responsible for setting the strategic direction, architectural vision, and execution of the organization's enterprise data engineering initiatives. This role oversees the design, implementation, and optimization of large-scale, complex data platforms that support advanced analytics, artificial intelligence, and business intelligence solutions. The Principal Data Engineer guides the adoption of state-of-the-art data technologies and methodologies, ensuring robust, scalable, and secure data pipelines that seamlessly integrate structured and unstructured data sources across the organization. In addition to hands-on technical contributions, this position provides thought leadership, mentors engineering teams, and collaborates with executive stakeholders to align data engineering strategies with organizational goals. The Principal Data Engineer also leads research and innovation to continuously advance the company's data engineering capabilities and competitive advantage.

Job Responsibilities

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.

Qualification Requirements

Basic 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.

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.
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.

Get to know Syneos Health

Over the past 5 years, we have worked with 94% of all Novel FDA Approved Drugs, 95% of EMA Authorized Products and over 200 Studies across 73,000 Sites and 675,000+ Trial patients.

No matter what your role is, you'll take the initiative and challenge the status quo with us in a highly competitive and ever-changing environment. Learn more about Syneos Health.

http://www.syneoshealth.com

Additional Information

Tasks, duties, and responsibilities as listed in this job description are not exhaustive. The Company, at its sole discretion and with no prior notice, may assign other tasks, duties, and job responsibilities. Equivalent experience, skills, and/or education will also be considered so qualifications of incumbents may differ from those listed in the Job Description. The Company, at its sole discretion, will determine what constitutes as equivalent to the qualifications described above. Further, nothing contained herein should be construed to create an employment contract. Occasionally, required skills/experiences for jobs are expressed in brief terms. Any language contained herein is intended to fully comply with all obligations imposed by the legislation of each country in which it operates, including the implementation of the EU Equality Directive, in relation to the recruitment and employment of its employees. The Company is committed to compliance with the Americans with Disabilities Act, including the provision of reasonable accommodations, when appropriate, to assist employees or applicants to perform the essential functions of the job.

Summary

Job Summary The Principal Data Engineer is a senior technical leader responsible for setting the strategic direction, architectural vision, and execution of the organization's enterprise data engineering initiatives. This role oversees the design, implementation, and optimization of large-scale, complex data platforms that support advanced analytics, artificial intelligence, and business intelligence solutions. The Principal Data Engineer guides the adoption of state-of-the-art data technologies and methodologies, ensuring robust, scalable, and secure data pipelines that seamlessly integrate structured and unstructured data sources across the organization. In addition to hands-on technical contributions, this position provides thought leadership, mentors engineering teams, and collaborates with executive stakeholders to align data engineering strategies with organizational goals. The Principal Data Engineer also leads research and innovation to continuously advance the company's data engineering capabilities and competitive advantage.