Job Description: Data Engineer – PySpark

Company: ZAGENO
Role: Data Engineer – PySpark / Data Platform
Experience: 3+ years
Employment Type: Full-time
Primary Skills: Python, SQL, PySpark, Databricks, Delta Lake, Apache Airflow, Change Data Capture (CDC)
Location: Bangalore
Notice Period Preference: Candidates who can join within 30 days are preferred.

About ZAGENO
ZAGENO is a digital platform focused on simplifying the procurement of life-sciences research products. Reliable, accurate, and well-structured product data is essential to helping researchers and life-sciences organizations discover and procure the products they need.

We are looking for a hands-on Data Engineer with strong PySpark expertise and proven production pipeline ownership to strengthen the reliability, scalability, and correctness of our data platform.

In this role, you will work on the data pipelines and systems that power our life-sciences product catalog. You will address existing pipeline failures and technical debt, build effective data synchronisation mechanisms, improve product data quality,



and develop maintainable data products for business and technical stakeholders.

This is an engineering role for someone who enjoys solving real production problems, taking ownership from design through deployment, and building reliable systems that scale.

Role Overview
As a Data Engineer, you will own the design, development, testing, deployment, and operational reliability of production-grade data pipelines.

You will work with large and complex datasets using PySpark, Python, SQL, Databricks, Delta Lake, and Apache Airflow. You will also build and maintain change data capture (CDC) workflows, low-latency APIs, and data synchronisation processes.

A key part of the role involves transforming inconsistent product and supplier data into standardised, accurate, and reusable datasets. You will collaborate with Catalog Operations, Analytics, Data Science, and other business stakeholders to translate

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