Senior Data Engineer – Azure

Jobtailor

Pune District

On-site

INR 1,500,000 - 2,100,000

Full time

14 days+

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Job summary

Jobtailor in Pune is seeking a data engineering professional with 5–8 years of experience to design and manage cloud-based data pipelines. You will work with Azure Databricks, Data Factory, ADLS2 and SQL to build robust ETL processes, ensure data quality, and support production environments. Strong communication and problem-solving skills are essential.

The role emphasizes live data pipelines, governance concepts, and potential exposure to ML engineering pipelines within Azure ML services.

Qualifications

  • 5–8 years of data engineering experience in modern cloud environments.
  • Excellent communication and team attitude.
  • Hands-on with PySpark, Python and SQL in cloud data platforms.
  • Experience with Azure Databricks, Data Factory and data lakes.
  • Strong troubleshooting skills across Python, Azure and SQL.
  • Experience with live data pipelines and production support.
  • Understanding of data quality, governance and MDM concepts.
  • Nice to have ML engineering pipelines and Azure ML services.

Skills

Data engineering
SQL knowledge
ETL development
Troubleshooting
Live data pipelines
Production support
Communication

Tools

Azure Databricks
Python
Azure Data Factory
ADLS2
Azure
Function Apps
Logic Apps
Azure ML services

Job description

Requirements
  • 5-8 Years in Data Engineering skillsets
  • Excellent Communication and Attitude
  • Working experience in Azure Databricks, Python, Azure Data Factory, ADLS2, Azure, Function Apps, Logic apps
  • Strong SQL Knowledge and worked with multiple SQL databases
  • Good ETL Skills and worked on code from scratch
  • Strong Troubleshooting and Debugging skills in python/Azure/SQL
  • Worked on Live Data Pipelines and supported in production environment
  • Understand Data Quality, Governance and MDM concepts
  • Nice to Have:
    • Worked on ML engineering pipelines
    • Worked on Azure ML services
    • Good Data Analysis skills
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