Software Engineer (Data Engineering)

Location: Bangalore, India

About nference

nference is an AI-first healthcare technology company dedicated to accelerating biomedical discovery and transforming healthcare through cutting-edge artificial intelligence and large-scale computing. Our platforms help pharmaceutical companies, healthcare providers, and research organizations unlock insights from complex clinical, molecular, and imaging data to drive better decisions and improve patient outcomes.

Founded with the vision of solving some of healthcare’s most challenging problems, nference combines deep expertise in software engineering, machine learning, data science, and life sciences to build products that make a meaningful impact on global healthcare. Recognized by The Washington Post as the “Google of Biomedicine,” we continue to push the boundaries of innovation by partnering with leading healthcare institutions and industry pioneers.

Our People

Our people are our greatest strength. At nference, you’ll work alongside exceptional software engineers, AI researchers, physicians, scientists, and product leaders who are passionate about solving meaningful, real-world problems.

We foster a culture built on ownership, curiosity, collaboration, and continuous learning. Engineers are encouraged to challenge assumptions, contribute ideas, influence technical direction, and take ownership of their work from concept to production. Whether you’re building scalable data pipelines, enabling analytics platforms, or developing cloud-native data solutions, you’ll collaborate with some of the brightest minds in technology and healthcare.

The Opportunity

We’re looking for a Software Engineer (Data Engineering) who is passionate about building scalable data pipelines and enabling reliable, high-quality data platforms. In this role, you’ll contribute to the development of data ingestion, transformation, and orchestration workflows that power our AI-driven healthcare products.

You’ll collaborate closely with software engineers, data scientists, AI researchers, and product teams to solve data engineering challenges while building reliable, maintainable, and scalable data solutions. This role is ideal for someone who enjoys working with data, cloud technologies, and modern data engineering tools.

What You’ll Do

• Build and maintain batch ETL/ELT pipelines to ingest and transform data from internal and external sources.
• Write and optimize SQL queries for data cleaning, transformation, and aggregation.
• Implement data quality checks, including schema validation, null checks, and deduplication within data pipelines.
• Support orchestration workflows using Airflow, dbt, ADF, or similar tools by scheduling, monitoring, and troubleshooting job runs.
• Debug pipeline failures using logs and resolve issues related to data inconsistencies, schema changes, or infrastructure failures.
• Collaborate with analysts, data scientists, backend engineers, and cross-functional teams to understand and deliver data requirements.
• Work with cloud data platforms such as Snowflake, BigQuery, or Amazon Redshift for data storage and querying.
• Contribute to data modeling using fact and dimension tables while maintaining documentation for datasets and pipelines.
• Automate repetitive data engineering tasks using Python and scripting.
• Continuously improve data pipeline reliability, scalability, and operational efficiency.

What We’re Looking For

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related technical discipline.
• 1–3 years of professional experience in Software Engineering, Data Engineering, or a related role.
• Proficiency in Python (preferred) or another programming language.
• Strong knowledge of SQL.
• Working knowledge or exposure to orchestration tools such as Apache Airflow, dbt, Azure Data Factory (ADF), or similar technologies.
• Basic understanding of ETL/ELT concepts and data pipeline workflows.
• Familiarity with relational databases and data warehousing concepts, including fact and dimension tables.
• Exposure to at least one cloud platform (AWS, Google Cloud Platform (GCP), or Microsoft Azure) and cloud data warehouses.
• Basic debugging skills for identifying and resolving data and pipeline issues.
• Basic understanding of database performance optimization and query tuning.
• W…