Senior Big Data/Machine Learning Engineer

Plano, TX, US • Posted 5 hours ago • Updated 5 hours ago
Full Time
On-site
USD $65.00 - 75.00 per hour
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Big Data
  • FOCUS
  • Scalability
  • Collaboration
  • SLA
  • Continuous Improvement
  • Computer Science
  • Information Technology
  • Extract
  • Transform
  • Load
  • Java
  • Python
  • SQL
  • Real-time
  • Streaming
  • Data Processing
  • Apache Kafka
  • Apache Spark
  • Apache Hadoop
  • Electronic Health Record (EHR)
  • Data Warehouse
  • Cloud Computing
  • Amazon Web Services
  • Microsoft Azure
  • Google Cloud Platform
  • Google Cloud
  • Workflow
  • Scheduling
  • Orchestration
  • Management
  • Agile
  • Data Engineering
  • Performance Tuning
  • Data Quality
  • Regulatory Compliance
  • Financial Services
  • Machine Learning (ML)
  • DevOps
  • Continuous Integration
  • Continuous Delivery
  • Communication
  • Stakeholder Management

Summary

  • Type: Contract
  • Job #105430

Job Title: Senior Big Data / Machine Learning Engineer

Location:
Plano, TX (Hybrid)

Schedule:
Full-Time, W2 Contract

Type:
W2 Contract Only (No C2C)

Duration:
Approximately 7 Months (Open-Ended)

Pay Rate:
$65-$75/hour W2

Relocation: Local candidates only. Relocation assistance is not available, and non-local candidates will not be considered.
Summary

We are seeking an experienced Senior Big Data / Machine Learning Engineer to design, build, and support enterprise-scale data platforms and real-time processing solutions. This role will focus on developing highly reliable, scalable batch and streaming data pipelines while collaborating with cross-functional Agile teams to deliver end-to-end data solutions. The ideal candidate will have strong experience with cloud technologies, distributed data processing frameworks, data orchestration platforms, and event-driven architectures.
Key Responsibilities
  • Design, develop, and maintain large-scale batch and real-time data pipelines that support enterprise data initiatives.
  • Build data ingestion, transformation, orchestration, and delivery solutions with an emphasis on scalability, performance, and reliability.
  • Develop and support event-driven architectures and real-time streaming solutions.
  • Collaborate with Agile teams to design end-to-end data engineering solutions from source systems through downstream consumption layers.
  • Optimize data processing workflows and improve overall platform performance.
  • Implement data quality, monitoring, observability, and alerting capabilities to ensure data reliability and SLA compliance.
  • Develop and maintain cloud-based data solutions leveraging modern data warehousing technologies.
  • Partner with stakeholders, architects, and engineering teams to translate business requirements into technical solutions.
  • Support secure credential management, secrets handling, and governance best practices across production environments.
  • Participate in code reviews, architecture discussions, and continuous improvement initiatives.
Required Qualifications
  • Must have a Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent professional experience.
  • 4+ years of experience building and supporting data pipeline and orchestration systems.
  • 4+ years of hands-on experience with Java, Python, and SQL.
  • 4+ years of experience working with real-time, streaming, or event-driven data platforms.
  • 4+ years of experience with distributed data processing technologies such as Kafka, Spark, Hadoop, EMR, or similar platforms.
  • 4+ years of experience working with cloud data warehousing solutions at scale.
  • 4+ years of experience utilizing cloud platforms including AWS, Azure, or Google Cloud Platform (Google Cloud Platform).
  • 3+ years of experience with workflow scheduling and orchestration tools.
  • 2+ years of experience with secure secrets management and credential handling in production environments.
  • 2+ years of experience working within Agile software development teams.
  • Strong understanding of data engineering best practices, performance optimization, and scalable architecture design.
Preferred Qualifications
  • Experience implementing data observability frameworks, monitoring, alerting, and data quality solutions.
  • Background supporting highly regulated or compliance-driven industries, including financial services.
  • Familiarity with enterprise-scale machine learning platforms and model deployment pipelines.
  • Experience with DevOps, CI/CD automation, and infrastructure-as-code practices.
  • Strong communication and stakeholder management skills.
  • Experience designing highly available, fault-tolerant data platforms.

#INDPRO
#LI-JC1
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10111081
  • Position Id: 85286024bc4abee479c48e9d0d683676
  • Posted 5 hours ago
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