Top 109 Python developer Jobs in Utah

Senior Big Data/Machine Learning Engineer
Epitec —United States
- $65 - $75 an hour
- Contract
- Azure
- Computer Science
- Java
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Senior Big Data/Machine Learning Engineer

Epitec -
United States

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Job Details

Contract
$65 - $75 an hour
8 days ago

Qualifications

Commercial use (data warehousing systems)
Performance tuning
Software engineering
System performance optimization
Scalable systems
Enterprise software systems development
Java
Infrastructure architecture design
SQL
Data Architecture Design (Architecture design skills)
Production systems
Scalability
Agile software development
Cloud Architecture Design (Architecture design skills)
Data performance optimization
Batch data processing
Python
Stakeholder relationship building
Stakeholder management

Full Job Description

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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#LI-JC1

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