Senior Clinical Data Engineer

Zifo RnD Solutions; Tamil Nadu; On-site; INR 1,500,000 - 3,500,000; Full time

Job summary

TravelCenters of America is seeking a Senior Clinical Data Engineer to design, build, and manage scalable data pipelines for clinical trials. You will own end-to-end ingestion, integration, transformation, and delivery of clinical data from multiple sources into enterprise data platforms such as data lakes and data warehouses.

The role requires 5+ years in data engineering, strong Python/SQL skills, and hands-on AWS, Spark, and Airflow experience.

Qualifications

• Bachelor’s degree in Computer Science, IT, Engineering, Life Sciences or related discipline.
• 5+ years of experience in Data Engineering or related tech role.
• Strong hands-on programming with Python and SQL.
• Hands-on experience with AWS cloud platform.
• Experience designing and deploying production-grade ETL/ELT pipelines in cloud environments.
• Experience with Apache Spark.
• Experience with Apache Airflow.
• Data lakes/cloud data warehouses (Snowflake/Redshift).
• Understanding of SDLC and data integration concepts.
• Experience with JSON/XML and REST APIs.

Responsibilities

• Design, build, and manage scalable data pipelines for clinical trials.
• Ingest, integrate, transform, and deliver clinical data to data lakes/warehouses.
• Collaborate with clinical data teams, analytics teams, and downstream consumers.
• Ensure data reliability, traceability, quality and readiness for use.

Skills

Analytical thinking

Problem solving

Cross-functional collaboration

Data quality

Data modeling

Education

BE/BTech/BS/BA

Tools

Python

SQL

AWS

Apache Spark

Apache Airflow

Snowflake/Redshift

JSON/XML

REST APIs

GitLab/GitHub

Job description

We are looking for an experienced Senior Clinical Data Engineer to design, build, and manage scalable data pipelines supporting clinical trials.

In this role, you will be responsible for the end-to-end ingestion, integration, transformation, and delivery of clinical data from multiple source systems into enterprise data platforms such as data lakes and data warehouses. You will work closely with clinical data teams, analytics teams, and other downstream consumers to ensure that clinical data is reliable, traceable, high quality, and ready for use.

Requirements

• Bachelor's degree (BE/BTech/BS/BA) in Computer Science, Information Technology, Engineering, Life Sciences, Health Sciences, or a related discipline
• 5+ years of experience in Data Engineering, Software Engineering, or a related technology role
• Strong hands-on programming experience with Python and SQL
• Hands-on experience with AWS cloud platform
• Experience designing and deploying production-grade ETL/ELT data pipelines in cloud environments
• Hands-on experience with distributed/big-data processing technologies such as Apache Spark
• Experience with workflow orchestration and scheduling using Apache Airflow
• Experience working with data lakes and/or cloud data warehouses, such as Snowflake or Amazon Redshift
• Strong understanding of database concepts, data modeling, data integration, and large-scale data processing
• Experience handling semi-structured data formats such as JSON and XML
• Experience building or consuming REST/API-based integrations
• Familiarity with source control and CI/CD tools such as GitLab/GitHub
• Strong understanding and practical application of the Software Development Life Cycle (SDLC)

Clinical Domain Experience

• Experience working with clinical trial data and clinical data workflows
• Familiarity with clinical systems and data sources such as EDC/eCRF, CTMS, and other clinical trial source systems
• Ability to understand study-level data requirements and translate them into scalable technical solutions
• Experience coordinating or supporting study-level data transfer and integration specifications is preferred
• Understanding of data quality, traceability, validation, and regulatory expectations within a clinical environment is highly desirable

Key Competencies

• Strong analytical and critical-thinking skills
• Excellent problem-solving and troubleshooting abilities
• Ability to independently own technical deliverables while working effectively within cross-functional teams
• Strong communication skills with the ability to collaborate with both technical and clinical stakeholders
• Ability to understand complex data requirements and translate them into practical engineering solutions
• Strong focus on data quality, reliability, scalability, and automation
• Ability to manage priorities and deliver within clinical study timelines

Technology Landscape

• Programming: Python (Advanced)
• Big Data: Apache Spark
• Orchestration: Apache Airflow
• Cloud: AWS
• Data Platforms: Amazon Redshift / Data Lakes
• Databases: SQL
• Data Integration: REST APIs, JSON, XML, file-based integrations
• DevOps: GitLab / GitHub, CI/CD
• Clinical Systems: EDC/eCRF, CTMS, clinical source systems