Data Engineer - Oakbrook Terrace

Only for registered members Oakbrook Terrace, United States

3 days ago

Default job background
$80,000 - $140,000 (USD) per year *
* This salary range is an estimation made by beBee
Title: · Data Engineer · Location: · Onsite in Oakbrook Terrace, IL · Terms of Employment · W2 Contract, 12 months · The office is located in Oakbrook Terrace, IL. · OverviewOur Client is seeking a mid-level Data Engineer is responsible for designing, building, and maintaining th ...
Job description

Title:
Data Engineer

Location:
Onsite in Oakbrook Terrace, IL

Terms of Employment


  • W2 Contract, 12 months
  • The office is located in Oakbrook Terrace, IL.
Overview

Our Client is seeking a mid-level Data Engineer is responsible for designing, building, and maintaining the data infrastructure and pipelines that enable efficient data processing, storage, and analysis within a hybrid computing environment.

This role bridges the gap between data collection and data consumption across both high-performance computing (HPC) servers and Azure cloud platforms, ensuring that data is accessible, reliable, and optimized for analytics, machine learning, and business intelligence purposes.

Responsibilities


  • Design, develop, and implement scalable data pipelines using modern ETL/ELT frameworks and tools in hybrid environments
  • Create and maintain data architectures that span high-performance computing servers and Azure cloud services
  • Build robust data integration solutions to connect various data sources across on-premises and cloud systems
  • Configure and optimize databases and data stores in both UNIX/Linux environments and cloud platforms
  • Implement MLOps practices to support the machine learning lifecycle from development to production
  • Design and implement modern data flow architectures that support both batch and real-time processing needs
  • Apply performance tuning techniques for high-volume data processing in HPC environments
  • Collaborate with data scientists, ML engineers, and business stakeholders to understand data requirements
  • Develop and maintain documentation for data infrastructure, pipelines, and workflows
  • Implement data quality monitoring and validation across hybrid environments
  • Mentor junior data engineers on best practices for hybrid cloud/on-premises architectures
Required Skills & Experience


  • Bachelor's degree in Computer Science, Information Systems, or related technical field
  • Relevant certifications in Azure, data technologies, or HPC administration
  • 3-5 years of experience in data engineering or related field
  • Strong UNIX/Linux administration skills and command-line proficiency
  • Experience with high-performance computing environments and workload management
  • Proficiency in SQL and experience with major database systems (PostgreSQL, SQL Server, Oracle, MySQL)
  • Hands-on experience with Azure cloud data services (Azure Data Factory, Synapse Analytics, Azure SQL)
  • Knowledge of modern data flow architectures (Lambda, Kappa, Delta) and implementation patterns
  • Experience with ML flow frameworks and ML lifecycle management tools
  • Programming skills in Python and shell scripting for automation and data processing
  • Familiarity with containerization (Docker) and orchestration (Kubernetes)
  • Experience with data processing frameworks (Spark, Databricks, Azure Batch)
  • Understanding of networking concepts for data movement between on-premises and cloud
Preferred Skills & Experiment


  • Experience with real-time data processing and streaming technologies (Kafka, Event Hubs)
  • Knowledge of infrastructure-as-code tools (Terraform, ARM templates)
  • Experience with distributed file systems (HDFS, Lustre) and object storage
  • Familiarity with graph databases and specialized analytics datastores
  • Understanding of data governance, security, and compliance requirements across hybrid environments
  • Experience with optimization techniques for large-scale data transfers between systems
  • Knowledge of GPU acceleration for data processing pipelines
  • Background in implementing CI/CD for data solutions


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