Saturday, June 27, 2026

Urgent requiremnent of Senior Big Data Developer for O'Fallon, MO (Locals Only-F2F)

Hi,

 

This is Diksha Chaudhary working with Novia Infotech. We have the below contract job opportunity with one of our direct clients and would like to check if you have any resources available. Please send across the resume of your consultants along with the contact information at the earliest to diksha.c@noviainfotech.com.

 

Role: Senior Big Data Developer / Senior Data Engineer (Spark Scala)

Location: O'Fallon, MO (Local Candidates Only - F2F)

Duration: 12+ Months

Experience Required: 6–8+ Years

 

Description:

 

We are seeking a highly skilled Senior Big Data Developer / Senior Data Engineer with deep expertise in Apache Spark, Scala, PySpark, and real-time streaming architectures. The ideal candidate will design, build, and support large-scale batch and streaming data processing systems with a strong emphasis on Kafka-based streaming, Apache NiFi ingestion, and distributed object storage platforms such as Apache Ozone and Ceph.

This role is ideal for engineers who enjoy solving complex challenges related to scalability, low latency, performance optimization, fault tolerance, and production reliability in enterprise data platforms.


Mandatory Skills

Programming Languages

  • Scala
  • Python (PySpark)
  • SQL
  • Java (Core)
  • Unix Shell Scripting

Big Data Technologies

  • Apache Spark Core
  • Spark SQL
  • Spark Structured Streaming
  • Apache Spark Performance Tuning
  • Batch Processing
  • Real-Time Data Processing
  • Distributed Data Processing

Streaming Technologies

  • Apache Kafka
  • Kafka Streaming Architecture
  • Event-Driven Architecture
  • Real-Time Streaming Pipelines
  • Kafka Offsets and Partitions
  • Event Replay & Reprocessing

Data Ingestion & Orchestration

  • Apache NiFi
  • Apache Airflow
  • Data Ingestion Frameworks
  • Workflow Orchestration
  • Data Routing & Flow Management

Storage Technologies

  • Apache Ozone
  • Ceph
  • Distributed Object Storage
  • Object Storage Concepts
  • Large-Scale Data Storage Platforms

Databases & Data Processing

  • Structured Data
  • Semi-Structured Data
  • ETL Pipelines
  • ELT Pipelines
  • Data Validation
  • Data Reconciliation
  • Metadata Management

DevOps & Platform Engineering

  • Linux
  • Git
  • CI/CD Pipelines
  • Monitoring & Logging Tools
  • Automated Testing
  • Production Support

Key Responsibilities

Big Data Application Development

  • Design, develop, and maintain large-scale Apache Spark applications using:
    • Scala
    • PySpark
    • Spark SQL
  • Build highly scalable and fault-tolerant data processing frameworks.
  • Develop reusable components and data engineering frameworks.

Real-Time Streaming Architecture

  • Design and implement streaming data pipelines using:
    • Apache Kafka
    • Spark Structured Streaming
  • Build low-latency streaming applications supporting enterprise-scale data workloads.
  • Develop event-driven architectures for real-time analytics and data processing.

Advanced Streaming Patterns

  • Implement:
    • Stateful Streaming
    • Windowing
    • Watermarking
    • Late Data Handling
    • Checkpointing
  • Develop event replay and reprocessing mechanisms using Kafka offsets and partitions.
  • Ensure reliability and data consistency across streaming platforms.

Data Ingestion & Orchestration

  • Build and maintain ingestion and routing workflows using:
    • Apache NiFi
    • Apache Airflow
  • Implement Kafka-based ingestion patterns and orchestration pipelines.
  • Support large-scale data movement and processing frameworks.

ETL & ELT Pipeline Development

  • Develop end-to-end ETL and ELT pipelines.
  • Ensure:
    • Low Latency
    • Scalability
    • Fault Tolerance
    • High Availability
  • Design reusable and maintainable data processing frameworks.

Spark Performance Optimization

  • Optimize Spark applications through:
    • Partitioning Strategies
    • Memory Management
    • Shuffle Optimization
    • Efficient File Formats
    • CPU Optimization
    • I/O Tuning
  • Improve overall platform performance and resource utilization.

Storage Platform Integration

  • Integrate Spark workloads with:
    • Apache Ozone
    • Ceph
    • Distributed Object Storage Platforms
  • Design scalable storage architectures for analytics workloads.

Data Quality & Governance

  • Ensure:
    • Data Quality
    • Data Consistency
    • Auditability
    • Metadata Capture
  • Implement:
    • Validation Frameworks
    • Reconciliation Processes
    • Data Governance Controls

Production Support & Reliability Engineering

  • Support mission-critical production systems.
  • Perform:
    • Monitoring
    • Incident Management
    • Root Cause Analysis
    • Capacity Planning
    • Performance Optimization
  • Maintain strict SLA compliance.

Engineering Excellence

  • Contribute to:
    • Coding Standards
    • Reusable Frameworks
    • Architecture Reviews
    • Code Reviews
    • Technical Documentation
  • Promote engineering best practices and continuous improvement initiatives.

Required Qualifications

  • Bachelor's Degree in:
    • Computer Science
    • Engineering
    • Information Technology
    • Related Technical Discipline
  • 6–8+ years of experience in:
    • Big Data Engineering
    • Data Engineering
    • Distributed Systems
    • Real-Time Streaming Platforms
    • Enterprise Data Processing Systems
  • Strong hands-on experience with:
    • Apache Spark
    • Scala
    • PySpark
    • Spark Structured Streaming
    • Apache Kafka
    • Apache NiFi
  • Strong expertise in:
    • SQL Development
    • ETL/ELT Pipelines
    • Distributed Data Processing
    • Linux
    • Git
    • CI/CD
  • Experience working with:
    • Structured Data
    • Semi-Structured Data
    • Object Storage Platforms
    • Large-Scale Analytics Systems
  • Strong analytical, troubleshooting, and problem-solving skills.

Preferred Qualifications

Preferred Technologies

  • Apache Ozone
  • Ceph
  • Apache Airflow
  • AWS DevOps & Automation
  • Monitoring & Observability Platforms

Preferred Experience

  • Exactly-Once Processing Semantics
  • At-Least-Once Streaming Semantics
  • Streaming System Observability:
    • Consumer Lag
    • Throughput Monitoring
    • Backpressure Management
  • Mission-Critical Production Systems
  • High Availability Data Platforms
  • Automated Testing Frameworks

Key Competencies

  • Big Data Engineering
  • Real-Time Streaming Architecture
  • Distributed Systems Design
  • Performance Optimization
  • Fault-Tolerant Data Processing
  • Production Support
  • System Reliability Engineering
  • Problem Solving
  • Collaboration & Communication
  • Technical Leadership

 

 

'

Diksha Chaudhary
US IT Recruiter

www.noviainfotech.com 

E: diksha.c@noviainfotech.com
M: (972) 472-8161
A: McKinney, TX, 75070

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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