Principal Data Engineer- Hyderabad (Hybrid)

Syneos Health, Inc.; Hyderabad; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Syneos Health, Inc. is seeking a Principal Data Engineer in Hyderabad, TS, India. This senior role involves leading the strategic direction and architectural vision for enterprise data engineering initiatives. Candidates should have a Bachelor’s degree and at least 10 years of experience in data engineering, with proven abilities in Azure Databricks, Apache Spark, and ETL/ELT pipeline design. The position demands strong leadership in data solutions and best practices for data architecture, security, and compliance.

Qualifications

• Minimum of 10 years of experience in data engineering.
• Demonstrated expertise in designing and building ETL/ELT pipelines.
• Advanced proficiency in Python and SQL.

Responsibilities

• Lead the design and strategic planning of enterprise-wide data platforms.
• Establish best practices for data architecture and security.
• Mentor and coach data engineers within the organization.

Skills

Data modeling

Python

SQL

Azure Databricks

Apache Spark

Azure Data Factory

ETL/ELT pipelines

Git

Analytical skills

Problem-solving

Education

Bachelor’s degree in Computer Science, Engineering, Mathematics, or a closely related field

Master’s degree in Computer Science, Engineering, Mathematics, or a closely related field

Tools

ADF

Databricks

Spark

Job description

Updated: Today
Location: Hyderabad, TS, India
Job ID:25107940

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 position 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, the Principal Data Engineer provides thought leadership, mentors engineering teams, collaborates with executive stakeholders to align data engineering strategies with organizational goals, and 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), and use these technologies to build, optimize, and scale enterprise data solutions.
• Design and implement 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.

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 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.

The Company is committed to compliance with the Americans with Disabilities Act, including the provision of reasonable accommodations to assist employees or applicants in performing the essential functions of the job.