Remote Databricks Jobs – 70 Open Jobs Today

Data Engineer
Websenor —Remote
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Azure Data engineer
Princeton Software Services Pvt. Ltd. —Remote
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- Azure
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Snowflake Developer or Snowflake Migration Engineer with BI Connector Exp.
3Pillar —Remote
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Senior Data Engineer
Astegic —Remote
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- Computer Science
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Azure AI Data Engineer
Luxoft —Remote
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Data Engineering Technical Lead
Hillenbrand Corporate —Remote
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- Azure
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- Master's degree
Data Engineer Lead (OT Data)( Oil & Gas) (India)
Codvo.ai —Remote
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Senior Data Engineer (Snowflake, Azure & AI/ML)
WebSenor InfoTech —Remote
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Senior Data Engineer - Full Stack (US, Remote)
Codvo.ai —Remote
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Integration Engineer
LakeFusion —Remote
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- Azure
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Senior SAP Datasphere / BDC Developer
Infometry —Remote
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- Azure
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- Master's degree
Fullstack Data Engineer (India)
Codvo.ai —Remote
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Azure Data Engineer
Hanivisu Technologies —Remote
Strong experience in automating processes using Python, shell scripting, and working with Jenkins and Azure DevOps. Data Engineer: 6 years (Preferred).
₹1,00,000 - ₹1,20,000 a month
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6d
Azure Data engineer
Princeton Software Services Pvt. Ltd. —Remote
We are looking for a skilled Azure Data Engineer to design, build, and maintain scalable data pipelines and cloud-based data solutions on Microsoft Azure.
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Data Engineer

Websenor
Remote

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Job details

Full-time

Qualifications

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

Full job description

Data Engineer – Databricks | PySpark | Azure

Employment Type: Full-Time
Experience: 5–8 Years
Work Mode: Remote

Job Summary

We are looking for a skilled Data Engineer with strong hands-on experience in Databricks, PySpark, Delta Lake, Azure Data Factory (ADF), Azure Logic Apps, and Apache Airflow. The ideal candidate will be responsible for building scalable data pipelines, developing modern Lakehouse solutions, and implementing reliable workflow orchestration on Microsoft Azure.

The role will involve working with large-scale data processing, ETL/ELT development, pipeline optimization, data quality, and cloud-based data engineering solutions. This skill combination is commonly used for modern Azure data platforms and Databricks-based orchestration.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines using Databricks and PySpark.
Develop data transformation and processing solutions using Delta Lake.
Build and manage data integration pipelines using Azure Data Factory (ADF).
Create workflow automation and integrations using Azure Logic Apps.
Develop and manage Apache Airflow DAGs for scheduling and orchestration.
Integrate Airflow, ADF, Logic Apps, and Databricks for end-to-end workflow orchestration.
Work with ADLS Gen2 for data ingestion, storage, and processing.
Optimize Spark and Databricks workloads for performance, scalability, and cost efficiency.
Develop reusable frameworks for data ingestion, transformation, validation, and processing.
Implement data quality checks, monitoring, logging, alerting, and Data Observability practices.
Support CI/CD pipelines for data engineering code and deployment workflows.
Collaborate with Data Scientists, BI teams, Architects, and business stakeholders.
Prepare reliable and high-quality datasets for analytics and AI/ML workloads.
Support ML workflows and integrate MLflow where required.
Troubleshoot production issues and ensure data pipeline reliability and SLA adherence.
Follow best practices for data security, governance, version control, and documentation.

Required SkillsPrimary Skills

Databricks
PySpark
Delta Lake
Azure Data Factory (ADF)
Azure Logic Apps
Apache Airflow

Secondary Skills

Python
SQL
Azure Data Lake Storage Gen2 (ADLS Gen2)
CI/CD
MLflow
Data Observability
Microsoft Azure

Qualifications

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
4–8 years of experience in Data Engineering or a related role.
Strong hands-on experience developing production-grade data pipelines.
Good understanding of ETL/ELT concepts, data modeling, and Lakehouse architecture.
Strong problem-solving and analytical skills.
Good communication and collaboration skills.
Experience working in Agile/Scrum environments is preferred.

Preferred Qualifications

Experience with Azure Databricks and Azure-native data services.
Knowledge of Spark performance tuning and optimization.
Experience with event-driven and batch data processing.
Exposure to AI/ML data engineering or MLOps workflows.
Experience with Git, Azure DevOps, GitHub Actions, or similar CI/CD tools.
Knowledge of data governance, lineage, and data quality frameworks.
Databricks or Azure certifications are a plus.

Work Location: Hybrid remote in Remote

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