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