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Senior Data Engineer

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Remote

Senior Data Engineer

Maganti IT Resources, LLC

Senior Data Engineer

Skills

Google Cloud PlatformSQL QueriesData EngineeringPythonData AnalysisMachine LearningAIAWSPySparkComplianceAzure

7 days ago

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Important information


Contract type:

Freelance / Contract

Location:

Columbus, OH, USA

Work mode:

Remote

Published on:

15 October 2026

What they need


REMOTE : SR. DATA Engineer WIT AI

Location: Columbus, Ohio (local Candidates will Preferred )

RATE $60 on w2

MIN EXP 10-15 years

Job Summary

Safelite is seeking an experienced Data Engineer with expertise in data pipeline development, cloud data platforms, and AI/ML data integration. The ideal candidate will design, develop, and maintain scalable data engineering solutions that support analytics, machine learning, and AI-driven business applications.

The candidate will collaborate with data scientists, software engineers, and business stakeholders to build reliable data pipelines, optimize data processing, and ensure high-quality data availability for enterprise reporting and intelligent automation initiatives.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.

Build and optimize data workflows using Python, SQL, and Apache Spark/PySpark.

Develop data integration solutions across cloud platforms and enterprise systems.

Support AI/ML initiatives by preparing, transforming, and validating datasets for model training and inference.

Build data pipelines supporting generative AI, large language models (LLMs), and retrieval-augmented generation (RAG) applications, where applicable.

Work with cloud data platforms such as AWS, Microsoft Azure, or Google Cloud Platform.

Implement data quality checks, monitoring, logging, and error-handling mechanisms.

Optimize data storage, query performance, and processing efficiency.

Collaborate with data scientists and ML engineers to operationalize machine learning models.

Implement data governance, security, access controls, and compliance standards.

Use CI/CD pipelines, Git, and automated testing to support reliable data deployments.

Troubleshoot data pipeline issues and improve overall system performance.

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