Principal Data Engineer

Principal Data Engineer

Principal-level Java engineer to design and build enterprise-grade, real-time and batch data processing systems using Java, Spark, Kafka, and Microservices architecture. Strong focus on event-driven pipelines, API development (build + consume), and high-volume streaming platforms.

Architect, design, and implement enterprise-grade Java-based data platforms and distributed processing systems

Build and maintain production-ready Spark applications (Java) for batch and real-time processing

Design and evolve Kafka-based event streaming and ingestion pipelines

Develop and consume REST APIs within microservices architecture

Lead architecture ensuring scalability, reliability, and regulatory compliance

Apply strong object-oriented design and engineering practices

Mentor engineers on performance tuning and production readiness

Design and implement MDM solutions (match, merge, survivorship logic)

Ensure data quality, observability, and system stability

Support production deployments and operational handoffs

10–12+ years experience in Java/backend or data engineering

Hands-on experience building real-time data pipelines (Kafka, Spark Streaming/Flink)

Solid knowledge of relational databases (Redshift, PostgreSQL, Snowflake) and NoSQL databases (MongoDB or similar)

Strong Kafka and event-driven architecture experience

Strong Microservices experience (Spring Boot, REST APIs)

Experience in API development and API consumption

Hands-on Spark experience (batch and streaming)

Strong SQL and data modeling skills

AWS experience (S3, Glue, EMR, Redshift)

Experience in regulated/data governance environments

CI/CD, Git, Docker/Kubernetes familiarity

Candidates must have hands-on experience building real-time/event-driven data pipelines using Kafka and Spark/Flink, along with strong microservices and API development experience.