Engineer II - Hyderabad-Hybrid

Syneos Health® is a leading fully integrated biopharmaceutical solutions organization built to accelerate customer success. We translate unique clinical, medical affairs and commercial insights into outcomes to address modern market realities.  

Every day we perform better because of how we work together, as one team, each the best at what we do. We bring a wide range of talented experts together across a wide range of business-critical services that support our business. Every role within Corporate is vital to furthering our vision of Shortening the Distance from Lab to Life®.

Discover what our 29,000 employees, across 110 countries already know.

WORK HERE MATTERS EVERYWHERE

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 our Total Self culture – where you can authentically be yourself. Our Total Self culture is what unites us globally, and we are dedicated to taking care of our people. 
• We are continuously building the company we all want to work for and our customers want to work with. Why? Because when we bring together diversity of thoughts, backgrounds, cultures, and perspectives – we’re able to create a place where everyone feels like they belong. 

Job Responsibilities

The Engineer II is a highly skilled individual contributor responsible for designing, building, and optimizing scalable data and AI platforms. This role focuses on modern cloud-based data engineering solutions on Azure, enabling advanced analytics, AI/ML workloads, and intelligent applications. The engineer will collaborate closely with data engineers, platform teams, and business stakeholders to deliver reliable, high-performance data solutions and AI-enabled

systems.

Core Responsibilities

• Design, develop, and maintain scalable data pipelines and architectures using Azure Data Factory (ADF), Azure Databricks, and Azure-native services.

• Build and optimize ETL/ELT workflows for structured and semi-structured data at scale.

• Develop high-quality, production-grade code using Python, PySpark, and SQL,

following best practices for performance, security, and maintainability.

• Implement data processing and transformation logic in Databricks leveraging Spark optimizations.

• Design and implement secure, scalable APIs to expose data from Azure Databricks and cloud storage platforms for seamless integration with downstream applications and services.

• Design and implement Retrieval-Augmented Generation (RAG) pipelines and AI agents, integrating vector databases, embeddings, and LLMs where applicable.

• Support model fine-tuning and integration of ML/AI models into production data pipelines and applications.

• Collaborate with cross-functional teams to translate business requirements into technical solutions.

• Ensure data quality, reliability, observability, and cost efficiency across data platforms.

• Contribute to platform standards, reusable frameworks, and engineering best practices.

Education Requirements

Minimum 4 Year / Bachelors

Degree - Bachelor’s degree in computer science, Engineering, or a related field; advanced degree preferred

Qualifications

• Strong hands-on experience with Azure cloud services, specifically:

o Azure Databricks

o Azure Data Factory (ADF)

• Advanced proficiency in Python, PySpark, and SQL for data processing and analytics.

• Solid understanding of data modeling, distributed computing, and performance optimization.

• Experience working with large-scale datasets in cloud-based environments.• Strong problem-solving skills and ability to work independently in complex technical environments.

Preferred / Nice-to-Have Qualifications

• Hands-on experience building RAG-based solutions and AI agents using modern LLM frameworks.

• Experience with fine-tuning foundation models and integrating them into enterprise workflows.

• Familiarity with vector databases and embedding-based search solutions.

• Experience developing lightweight applications or dashboards using Streamlit, Dash, or Flask.

• Exposure to CI/CD pipelines, infrastructure as code, and MLOps/DataOps practices.

Level Expectations – Engineer II

• Operates independently on complex engineering tasks

• Owns end-to-end delivery of medium to large technical initiatives

• Influences design decisions and technical direction within the team

Years of Experience

5+ years of relevant professional experience in data engineering or related roles.

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.