Role Overview :

In this role you will own the reliability and performance of operational pipelines across our product catalog infrastructure. You will identify and reduce technical debt, replacing reactive patches with designed, testable logic.

Key Responsibilities :

- Build and maintain low latency data APIs that serve downstream operational and analytics consumers.
- Implement CDC patterns to keep catalog data synchronized across systems with minimal lag.
- Build monitoring, observability, and automated testing so failures surface before stakeholders report them.
- Design and implement unit standardization and master data logic at catalog scale.
- Translate business requirements from non-technical stakeholders into durable pipeline logic.
- Own code versioning, deployment, and incident response for your layer.

Tech Stack :

BigQuery, Databricks, Spark/PySpark, AWS/GCP.

What we're looking for :

- 3+ years as a Data Engineer, including solo or primary ownership of production pipelines.
- Strong Python - data engineering,



transformation logic, testing discipline.
- Robust SQL with ability to write correct queries, identify and refactor anti-patterns.
- Databricks, Delta Lake, Airflow for production orchestration.
- Experience with CDC patterns for real-time or near-real-time data synchronization.
- Experience building low latency APIs serving operational or analytical consumers.
- Test-driven development discipline - unit tests, integration tests, regression coverage as standard practice.
- Operates independently under ambiguity; designs systems to be maintained, not just to run.

Preferred Qualifications :

- Kafka or equivalent event streaming platform experience.
- Experience with entity matching, deduplication, or master data management.
- Exposure to ML pipeline support in production.
- Familiarity with NLP techniques for entity resolution or text normalization.

📌 Data Engineer - Python/SQL (India)
🏢 Human Touch
📍 India