Big Data Engineer

Title: Big Data Engineer x3
Location: Hybrid in Iselin, NJ (3 days onsite)

We can take relocation candidates as long as they can relocate and do an onsite interview


Overview
We are seeking an experienced Big Data Developer with strong Python expertise and hands-on experience building scalable data processing pipelines. The ideal candidate will have deep knowledge of distributed compute engines such as Apache Spark, modern lakehouse architectures, and real-time streaming platforms. Exposure to emerging Agentic AI frameworks is a valuable plus.
Key Responsibilities

• Design, develop, and optimize data processing pipelines using Apache Spark and PySpark.
• Build and maintain batch and streaming data loads for large-scale data platforms.
• Implement robust data models and storage layers using Lakehouse/Object Store technologies.
• Work with modern table formats such as Apache Iceberg or Delta Lake to support scalable data operations.
• Develop SQL-based transformations and ensure data quality, consistency, and performance.
• Integrate and manage Kafka for real-time data ingestion and event streaming.
• Collaborate with cross-functional teams including data engineering, analytics, and platform engineering.
• Participate in architectural discussions, code reviews, and performance tuning.
• (Nice to Have) Contribute to prototypes or solutions leveraging Agentic AI frameworks such as LangGraph, LangChain, or A2A.

Required Qualifications

• 6+ years of experience as a Big Data Developer or Data Engineer.
• Strong hands-on experience with Python, including data processing and automation.
• Expertise with Apache Spark and PySpark, including building scalable ETL/ELT pipelines.
• Experience working with Lakehouse/Object Store architectures (e.g., S3, ADLS, GCS).
• Proficiency with modern table formats such as Iceberg or Delta Lake.
• Strong SQL skills and experience with relational data modeling.
• Practical experience with Kafka for distributed messaging and streaming.
• Solid understanding of distributed systems, data partitioning, and performance optimization.