
Building Scalable Data Infrastructure
1 day ago
Job Title: Architect of Scalable Data Systems
About the RoleWe are seeking an experienced Technical Lead to architect, implement, and scale our end-to-end data platform. The successful candidate will lead a small team of engineers and work cross-functionally with stakeholders to enable reliable, timely, and secure data access across the business.
Key Responsibilities- Design and scalability of the data lake architecture for streaming and batch workloads.
- Lead the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark.
- Structure and evolve data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries.
- Drive data productization and enable API-first and self-service access to curated datasets.
- Define and track SLAs and SLOs for critical data pipelines.
- Collaborate with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance.
- At-least 7 years of experience in data engineering.
- Deep hands-on experience with AWS data stack: Glue, S3, Athena, Lake Formation, DMS, and Redshift Spectrum.
- Expertise in designing data pipelines for real-time, streaming, and batch systems.
- Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation.
- Experience working in a regulated environment with audit logging and data retention requirements.
- Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection.
- Familiarity with data contracts, data mesh patterns, and data as a product principles.
- Dynamic and innovative culture that fuels growth, creativity, and collaboration.
- Focus on employee development, supporting continuous learning and growth.
- Encourage speaking up, sharing ideas, and taking ownership.
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