Senior Big Data Engineer - Hybrid (Spark/Hadoop)

KMM Technologies, Inc.; Rockville (MD); Hybrid; USD 140,000 - 200,000; Full time

Job summary

KMM Technologies, Inc. in Rockville, MD / Tysons, VA is seeking a Senior Big Data Engineer with 12+ years of experience to design, implement, and optimize large-scale data pipelines. The role requires expertise in distributed systems, cloud platforms, and modern big data tech stacks including Hadoop and Spark.

Hybrid work with three onsite days per week is offered. The ideal candidate will collaborate with data scientists and analysts to enable data-driven decisions, ensure scalability, and

Qualifications

• Bachelor's degree in CS/IS or related field, 5+ years experience required, 12+ years noted in posting.
• Proficiency with distributed data processing systems and cloud platforms.
• Strong written and verbal technical communication skills.
• Experience with Agile development methodologies.
• Past financial services industry experience preferred.
• Proficiency in Java, Scala, or Python.

Responsibilities

• Design, develop, and maintain large-scale data processing pipelines using Hadoop, Spark, Python or Scala.
• Implement data ingestion, storage, transformation, and analysis solutions that are scalable and reliable.
• Stay current with industry trends and emerging Big Data technologies to improve data architecture.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Optimize and enhance existing data pipelines for performance and reliability.
• Develop automated testing frameworks and continuous testing for data quality.

Skills

Big Data

Distributed systems

Java

Scala

Python

SQL

Education

Bachelor's degree in Computer Science / Information Systems

Master's degree (preferred)

Tools

Hadoop

Spark

Hive

Trino

AWS

Job description

KMM Technologies, Inc. in Rockville, MD / Tysons, VA is seeking a Senior Big Data Engineer with 12+ years of experience to design, implement, and optimize large-scale data pipelines. The role requires expertise in distributed systems, cloud platforms, and modern big data tech stacks including Hadoop and Spark.

Hybrid work with three onsite days per week is offered. The ideal candidate will collaborate with data scientists and analysts to enable data-driven decisions, ensure scalability, and