Novartis Hiring Associate Analyst in Hyderabad | Data Role

Summary

As an Associate Analyst, you will join a growing data engineering team that supports commercial analytics and data science use cases, with a strong focus on data quality, trust, and governance. This entry level role is designed for interns transitioning to full time roles and offers hands on exposure to modern data platforms, cloud technologies, and core data management and governance practices.

You will work under the guidance of senior data engineers, data quality leads, and managers to build, test, and maintain data pipelines. The role also involves applying data quality controls and supporting analytics teams with reliable and well governed datasets.

This position provides a solid foundation for building a long term career in data engineering, data quality, governance, and AI enablement within the life sciences domain.

Major Accountabilities

• Support development and maintenance of data ingestion and integration pipelines for analytics and reporting.
• Assist with implementing data quality checks, validations, and monitoring using defined technical and business rules across the data lifecycle.
• Help automate recurring data preparation, reconciliation, and validation tasks.
• Develop and improve data pipelines using Python and SQL under supervision while following established coding and quality standards.
• Support CI/CD processes for data pipelines including testing, version control, and documentation.
• Collaborate with data engineers, data quality analysts, solution architects, and external vendors to understand data solutions and best practices.
• Apply basic data management practices such as data modeling, harmonization, reference data usage, and standardized definitions.
• Maintain metadata, data lineage, and documentation to improve discoverability and transparency of datasets.
• Follow data governance, privacy, security, and FAIR data principles as applicable to assigned projects.
• Participate in requirement discussions and feasibility reviews with guidance while considering data quality and compliance needs.
• Assist analytics teams and end users by responding to data related queries and investigating basic data quality issues.
• Learn enterprise data platforms, data quality frameworks, governance processes, and life sciences data concepts through on the job training.

Minimum Requirements

• Bachelor’s degree or final year student converting from internship in Computer Science, Informatics, Engineering, Life Sciences, or a related discipline.
• 0 to 2 years of relevant experience through internships, academic projects, or hands on work in data, analytics, software development, or data management.
• Basic programming knowledge in Python and or SQL.
• Familiarity with relational databases and core data concepts including accuracy, completeness, and consistency.
• Exposure to cloud platforms, data engineering tools, data quality tools, or analytics tools through coursework or internships is beneficial.
• Basic understanding of software development lifecycle and Agile ways of working.

Desired Skills

• Foundational knowledge of data engineering and data pipelines.
• Understanding of data quality validation and governance concepts.
• Exposure to metadata management, data lineage, and documentation practices.
• Awareness of cloud based data platforms and BI or analytics tools.
• Interest in learning data engineering practices, DevOps basics, and cloud data integration.