Senior Big Data/Machine Learning Engineer

Epitec

$136K — $156K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, IT, Engineering, or equivalent experience
  • 4+ years building and supporting data pipelines and orchestration systems
  • 4+ years of hands-on experience with Java, Python, and SQL
  • 4+ years with real-time, streaming, or event-driven data platforms
  • 4+ years with distributed data processing technologies like Kafka, Spark, or Hadoop
  • 4+ years with cloud data warehousing solutions
  • Experience with cloud platforms such as AWS, Azure, or GCP.

Responsibilities

  • Design, develop, and maintain large-scale batch and real-time data pipelines
  • Build scalable, high-performing data ingestion and transformation solutions
  • Develop and support event-driven architectures and real-time streaming solutions
  • Collaborate with Agile teams for end-to-end data engineering solutions
  • Optimize data processing workflows for improved platform performance
  • Implement data quality and monitoring capabilities to ensure reliability
  • Develop cloud-based data solutions using modern warehousing technologies

Benefits

  • Access to advanced cloud technologies and data solutions
  • Opportunity to work in a collaborative Agile environment
  • Exposure to scalable architecture and best practices
  • Engagement in code reviews and architectural discussions
  • Hands-on experience with cutting-edge data processing frameworks
Full Job Description
  • 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 (GCP).
  • 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.

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