Remote Senior data engineer (snowflake, azure & ai/ml) Jobs – 8 Open Jobs Today

Senior Data Engineer (Snowflake, Azure & AI/ML)
WebSenor InfoTech —Remote
- Full-time
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WebSenor InfoTech —Remote
- Full-time
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- Computer Science
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Senior Data Engineer (Snowflake, Azure & AI/ML)

WebSenor InfoTech -
Remote

Quick apply

Job details

Full-time

Qualifications

BCS
CI/CD
Azure
Computer Science
Kubernetes
DevOps
Spark
Git
SQL
Bachelor's degree
Continuous integration
Scrum
GitHub
Agile
Apache
Data science
AI
Communication skills
Python
Information Technology

Full job description

Job Title

Senior Data Engineer

Experience

5+ Years

Employment Type

Full-Time

Work Mode

Remote

Job Summary

We are seeking an experienced Senior Data Engineer to design, develop, and maintain scalable enterprise data platforms and cloud-native data solutions. The ideal candidate will have strong expertise in Snowflake, Python, Azure, Spark, SQL, Airflow, and Kubernetes, with experience building high-performance data pipelines, supporting AI/ML model deployments, and enabling advanced analytics.

The successful candidate will collaborate with data scientists, analysts, and engineering teams to deliver reliable, secure, and scalable data solutions while ensuring high data quality and operational excellence. Experience in the Healthcare domain is highly preferred.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines and enterprise data workflows.
Build and optimize data pipelines using Snowflake, Python, SQL, Spark, and Azure.
Develop and manage workflow orchestration using Apache Airflow.
Design and implement cloud-based data solutions on Microsoft Azure.
Support deployment and operationalization of AI/ML models in production environments.
Optimize data processing performance, scalability, and reliability.
Manage and process structured and unstructured data from multiple sources.
Implement CI/CD best practices using GitHub.
Work with Kubernetes to deploy and manage containerized data applications.
Ensure data quality, governance, security, and compliance across enterprise platforms.
Troubleshoot production issues and provide ongoing support for data pipelines.
Collaborate with business stakeholders, data scientists, and cross-functional teams to deliver high-quality data solutions.

Required SkillsData Engineering

Snowflake
Python
SQL
Apache Spark
ETL/ELT Development
Data Pipeline Development
Data Modeling
Data Warehousing
Data Analytics

Cloud & DevOps

Microsoft Azure
Kubernetes
GitHub (CI/CD)
Apache Airflow

AI/ML

AI/ML Model Deployment
MLOps fundamentals
Production Model Support

Data & Analytics

Data Transformation
Data Integration
Performance Optimization
Data Quality & Validation
Troubleshooting & Production Support

Preferred Skills

Databricks
Healthcare domain experience
Experience with modern cloud data architectures
Knowledge of DevOps best practices
Exposure to Infrastructure as Code (IaC)

Required Qualifications

Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
5+ years of hands-on experience in Data Engineering.
Strong experience with Snowflake, Python, Azure, Spark, SQL, Airflow, Kubernetes, and GitHub CI/CD.
Experience deploying and supporting AI/ML models in production.
Strong understanding of cloud-based data engineering and analytics platforms.
Excellent analytical, problem-solving, and communication skills.
Ability to work effectively in a remote, collaborative environment.

Preferred Qualifications

Experience in the Healthcare domain.
Experience with Databricks.
Azure or Snowflake certifications.
Experience working in Agile/Scrum environments.

Success Measures

Successful delivery of scalable and reliable data engineering solutions.
High availability and performance of enterprise data pipelines.
Efficient deployment and monitoring of AI/ML models.
Improved data quality, governance, and operational efficiency.
Strong collaboration with cross-functional engineering and analytics teams.
Timely resolution of production issues and continuous platform enhancements.

Work Location: Hybrid remote in Remote

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