Description

You will design and scale data architectures for Wallet, Payments, and Commerce products, building pipelines for analytics and ML.

This role is hybrid.

Responsibilities

• Design and implement scalable batch and near-real-time data pipelines.
• Develop ETL/ELT workflows optimized for performance and cost.
• Implement dimensional data models and standardize business metrics.
• Instrument APIs and user journeys to capture behavioral and transactional data.
• Ensure data integrity, governance, privacy, and compliance.

Required Skills

• 6+ years of experience in data engineering for analytics or ML systems.
• Strong SQL proficiency.
• Experience in Python, Scala, or Java.
• Hands-on experience with Spark, Kafka, and Airflow.
• Strong understanding of data modeling and lakehouse architectures (e.g., Iceberg).
• Experience with AWS, Azure, or GCP.
• Experience with Snowflake, Databricks, Trino, or OLAP/NRT systems.
• Comfortable participating in rotating on-call.

Preferred Skills

• Familiarity with CI/CD, data observability, and infrastructure-as-code.
• Exposure to MLOps and GenAI/RAG pipelines, including LLM prompt engineering and fine-tuning.
• Experience in FinTech, Wallet, or Payments domain.

Key Skills

Education

Any Graduate