Principal Data Engineer

Description

Key Responsibilities

• Design and code robust data pipelines for batch and real-time use cases.
• Define data models, schemas, and evolution strategies for scalable systems.
• Implement reliable ingestion, transformation, and storage layers across cloud services.
• Work hands-on with event-driven architectures, microservices, and data APIs.
• Optimize data quality, performance, and observability.
• Partner with AI and backend teams to make data discoverable and usable in production.

Skills, Knowledge and Expertise

• 6+ years of hands-on experience in designing and building production data systems.
• Strong coding in Python and proficiency in SQL.
• Experience with data modeling, ETL/ELT, and data lifecycle management.
• Familiarity with event-driven systems (Kafka, Kinesis, or similar).
• Practical experience with cloud-native data workflows (AWS S3, Lambda, Glue, or similar).
• Solid understanding of structured, semi-structured, and unstructured data formats.

• Experience working with vector stores or retrieval-based pipelines.
• Familiarity with Lakehouse concepts (Delta/Iceberg/Hudi — or similar patterns).
• Understanding of data governance, cataloging, and lineage tracking.
• Exposure to ML data preparation or feature store design.

• Hands-on builder attitude: owns delivery from architecture to deployment.
• Collaborates across AI, backend, and DevOps teams.
• Provides mentorship through examples, not supervision.

About Emumba