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Data Engineer

Posted on: Nov 11, 2026

AIT Global inc
Columbus, Indiana
Onsite
Full-time

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Job Title :

Data Engineer

Job Type :

Full-Time

Job Location :

Columbus Indiana United States

Remote :

Job Description :

Job Title: Data Engineer
Location: Columbus, IN

This role requires strong expertise in Python, PySpark, Databricks, and Machine Learning/AI, along with hands-on experience in React, Node.js, Azure Web Applications, and OpenAI API integration. The engineer will design, build, and deploy scalable data quality and observability solutions - including AI/ML-powered validation

Deliverables:

Analyzing complex business systems, industry requirements, and/or data regulations
Processing and managing large data sets
Design and development for a Big Data platform using open source and third-party tools 4. Data Quality Engineering & Automation
Design and develop data quality profiling pipelines using PySpark, Python, and Databricks to ensure data accuracy and reliability.
Build automated validation, cleansing, and anomaly detection frameworks leveraging ML/AI models.
Integrate OpenAI APIs for intelligent rule generation, data summarization, and NLP-based insights.
Full-Stack Development (exp in Web & API)
Develop responsive React-based user interfaces for self-service data quality monitoring and visualization.
Build and maintain RESTful APIs using Node.js and Python (Flask/FastAPI) to serve ML models and DQ metrics.
Host and manage applications using Azure Web Apps, ensuring secure API connectivity and scalable architecture.
Cloud and Data Integration
Work with Azure SQL Database, Azure Storage, and Databricks for seamless data access and validation.
Integrate data pipelines with APIs, Dataverse, Snowflake, or other cloud data sources. 15. Support Azure Application Insights and monitoring integration for performance tracking. 16. ML/AI Enablement
Contribute to ML projects focused on data quality improvement and predictive monitoring.
Apply techniques like anomaly detection, clustering, or deep learning to identify data issues proactively.
Use OpenAI / LLM APIs to automate root cause analysis, data profiling, and rule suggestions. 20. Collaboration and Documentation
Partner with Data engineers, Architect team, Cloud support team and business stakeholders to translate requirements into technical solutions.
Document DQ frameworks, ML workflows, APIs, and integration processes for reusability and transparency.
SPARK, Scala/Java, Map-Reduce, Hive, Hbase, and Kafka or equivalent college coursework
SQL query language
Clustered compute cloud-based implementation experience
Developing applications requiring large file movement for a Cloud-based environment and other data extraction tools and methods from a variety of sources
Build analytical solutions 28. Experience with IoT technology, Experience in Agile software development
Manage Offshore delivery team from India, work assignment review, weekly report review with client

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Position Details

Posted:

Nov 11, 2026

Reference Number:

4609-8252

Employment:

Full-time

City:

Columbus

Job Origin:

CIEPAL_ORGANIC_FEED

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Job Title: Data Engineer
Location: Columbus, IN

Deliverables:

Analyzing complex business systems, industry requirements, and/or data regulations
Processing and managing large data sets
Design and development for a Big Data platform using open source and third-party tools 4. Data Quality Engineering & Automation
Design and develop data quality profiling pipelines using PySpark, Python, and Databricks to ensure data accuracy and reliability.
Build automated validation, cleansing, and anomaly detection frameworks leveraging ML/AI models.
Integrate OpenAI APIs for intelligent rule generation, data summarization, and NLP-based insights.
Full-Stack Development (exp in Web & API)
Develop responsive React-based user interfaces for self-service data quality monitoring and visualization.
Build and maintain RESTful APIs using Node.js and Python (Flask/FastAPI) to serve ML models and DQ metrics.
Host and manage applications using Azure Web Apps, ensuring secure API connectivity and scalable architecture.
Cloud and Data Integration
Work with Azure SQL Database, Azure Storage, and Databricks for seamless data access and validation.
Integrate data pipelines with APIs, Dataverse, Snowflake, or other cloud data sources. 15. Support Azure Application Insights and monitoring integration for performance tracking. 16. ML/AI Enablement
Contribute to ML projects focused on data quality improvement and predictive monitoring.
Apply techniques like anomaly detection, clustering, or deep learning to identify data issues proactively.
Use OpenAI / LLM APIs to automate root cause analysis, data profiling, and rule suggestions. 20. Collaboration and Documentation
Partner with Data engineers, Architect team, Cloud support team and business stakeholders to translate requirements into technical solutions.
Document DQ frameworks, ML workflows, APIs, and integration processes for reusability and transparency.
SPARK, Scala/Java, Map-Reduce, Hive, Hbase, and Kafka or equivalent college coursework
SQL query language
Clustered compute cloud-based implementation experience
Developing applications requiring large file movement for a Cloud-based environment and other data extraction tools and methods from a variety of sources
Build analytical solutions 28. Experience with IoT technology, Experience in Agile software development
Manage Offshore delivery team from India, work assignment review, weekly report review with client

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Data Engineer