Senior Big Data Engineer (Kubernetes / AWS / Spark) || In person interview || DC/VA/MD/NY/NJ

Nexiva Inc
Rockville, United States of America
10 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 237K

Job location

Rockville, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Big Data
Cloud Engineering
Program Optimization
Continuous Integration
DevOps
Distributed Systems
Elasticsearch
Python
Open Source Technology
Requirements Management
Scala
SQL Databases
Data Processing
Google Cloud Platform
Spark
Generative AI
Gitlab
Containerization
Kubernetes
Optimization Algorithms
Bitbucket
Data Management
Data Pipelines
Serverless Computing

Job description

  • Design, develop, and optimize data pipelines handling terabyte-scale datasets
  • Work with complex algorithms to process and analyze large volumes of data efficiently
  • Optimize code performance for scalability and high-throughput systems
  • Build and maintain containerized, serverless data platforms using Kubernetes
  • Support migration efforts from EMR/EC2-based systems to Kubernetes-based architecture
  • Maintain and enhance existing Kubernetes infrastructure
  • Develop and manage CI/CD pipelines using tools like GitLab and Bitbucket
  • Collaborate on requirements documentation, system design, and implementation
  • Contribute to emerging initiatives involving:
  • GenAI integration
  • AI agents and automation frameworks
  • Technologies such as Kiro (Amazon GenAI) and MCP (Model Context Protocol)

Technical Environment

  • Cloud Platforms: AWS (current), with exposure to Google Cloud and open-source ecosystems
  • Core Technologies:
  • Kubernetes (primary focus)
  • Elasticsearch
  • Big Data frameworks (EMR, distributed systems)
  • Programming Languages: Python, SQL, Scala (flexible)
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Requirements

  • Strong experience with Kubernetes, including deployment, migration, and infrastructure management
  • Experience working with large-scale data (terabytes) and distributed systems
  • Proficiency in at least one: Python, SQL, or Scala
  • Understanding of data processing optimization techniques
  • Familiarity with cloud-native architectures and containerization
  • Experience with CI/CD pipelines and modern DevOps practices
  • Exposure to AI/GenAI tools, agents, or related frameworks is a strong plus
  • AWS and/or Kubernetes certifications preferred

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