DATA ENGINEER - AI/ML

Diverse Lynx LLC
Minnetonka, MN, United States
15 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
4 years minimum
Compensation
$80,000.0 - $105,000.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Data Analysis Microsoft Azure Big Data Information Systems Data Architecture Information Engineering Data Governance Extract Transform Load (ETL) Data Transformation Dataspaces
+23 more
Data Systems Data Warehousing Distributed Computing Environment Python (Programming Language) Machine Learning Meta-Data Management Cloud Services DataOps Azure Machine Learning Scala (Programming Language) SQL Databases Feature Store Data Processing Feature Engineering Apache Spark Data Lakes Information Technology Data Lineage Real Time Data Data Management Machine Learning Operations Data Pipelines Devsecops

Job description

We are seeking a highly skilled Data Engineer to support enterprise AI/ML and Advanced Analytics initiatives by building scalable, reliable, and high-performance data platforms and pipelines. This role will focus on designing and engineering modern data solutions that enable machine learning, advanced analytics, and AI-driven decision making. The ideal candidate has strong expertise in data architecture, cloud platforms, large-scale data processing, and data engineering best practices. The successful candidate will build and Eligible to workimize data ecosystems that empower data scientists, analysts, and business teams to generate actionable insights and operational value., · Design, develop, and maintain scalable data pipelines supporting AI/ML and analytics workloads. · Build and Eligible to workimize batch and real-time data ingestion frameworks. · Develop data integration solutions across multiple internal and external data sources. · Engineer reliable datasets and feature stores that support machine learning model development. · Implement data transformation, cleansing, enrichment, and validation processes. · Design and maintain modern data lake, lakehouse, and data warehouse architectures. · Ensure data quality, integrity, security, and governance standards are met. · Eligible to workimize data processing performance, scalability, and operational efficiency. · Collaborate with Data Scientists and Analysts to support feature engineering and model deployment requirements. · Enable MLOps and ML platform capabilities to support model operationalization. · Implement monitoring, observability, and operational support processes for data platforms. · Maintain documentation, data lineage, and metadata management standards., Description Leidos is seeking a Lead DevSecOps Engineer to join the Air Traffic Business Area within the Homeland Sector, supporting the development of the Leidos Common Automati…

  • 10 days ago

Requirements

· Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Engineering, or related field. · 4+ years of experience in Data Engineering, Data Platforms, or Analytics Engineering. · Strong proficiency in Python, SQL, Spark, Scala, or equivalent technologies. · Experience building cloud-native data solutions using Azure, AWS, or Eligible to workP. · Experience with ETL/ELT frameworks and large-scale data processing. · Knowledge of distributed data processing technologies and modern data architectures. · Experience with data lake, warehouse, and lakehouse platforms. · Understanding of data governance, security, and data quality practices. · Strong collaboration and problem-solving skills.

Benefits & conditions

  • $87,100-157,450 per year

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