Azure Data Engineer

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profile Job Location:

Bangalore - India

profile Monthly Salary: Not Disclosed
Posted on: 30+ days ago
Vacancies: 1 Vacancy

Job Summary

Company Description

We are a consulting company with a bunch of technology-interested and happy people! We love technology we love design and we love quality. Our diversity makes us unique and creates an inclusive and welcoming workplace where each individual is highly valued. With us each individual is her/himself and respects others for who they are and we believe that when a fantastic mix of people gather and share their knowledge experiences and ideas we can help our customers on a completely different level. We are looking for you who is immediate joiner and want to grow with us! With us you have great opportunities to take real steps in your career and the opportunity to take great responsibility

Job Title: Azure Data Engineer

Experience: 810 Years
Location: PAN India (WFO)
Employment Type: Full-time

Role Overview

We are seeking an experienced Azure Data Engineer to design develop and optimize scalable data pipelines and analytics solutions on Microsoft Azure. The ideal candidate will have strong hands-on expertise with Azure Databricks Azure Data Factory Python and PySpark along with a solid understanding of data modeling ETL/ELT processes and best practices in data engineering.

Key Responsibilities

  • Design build and maintain end-to-end data pipelines using Azure Data Factory (ADF) and Azure Databricks.
  • Develop ETL/ELT frameworks and data transformation workflows using Python and PySpark.
  • Implement scalable data ingestion data cleansing data validation and data processing solutions.
  • Work with structured and unstructured datasets to build robust data engineering processes.
  • Optimize Databricks notebooks jobs clusters and workflows for performance and cost efficiency.
  • Implement Delta Lake data versioning and ACID transaction support for reliable pipelines.
  • Collaborate with data architects BI teams and analytics stakeholders to understand data requirements.
  • Ensure data quality data governance security and compliance across the data lifecycle.
  • Perform root-cause analysis troubleshoot issues and optimize pipeline reliability.
  • Create and maintain technical documentation design specifications and operational procedures.

Required Skills & Qualifications

  • Strong hands-on experience with Azure Databricks and ADB architecture including notebooks workflows Unity Catalog and Delta Lake.
  • Expertise in Azure Data Factory for orchestrating data pipelines.
  • Proficiency in Python and PySpark for data transformation and large-scale processing.
  • Solid understanding of ETL/ELT concepts data modeling and distributed data processing.
  • Experience working with Azure Storage (ADLS Gen2) Azure SQL and other Azure data components.
  • Familiarity with CI/CD for data pipelines using Git Azure DevOps or similar tools.
  • Strong debugging performance tuning and problem-solving abilities.
  • Excellent communication and collaboration skills.

Preferred Qualifications

  • Experience with Azure Synapse Analytics SQL Warehousing or Data Lakes.
  • Exposure to DataBricks Workflows MLFlow and Advanced Spark optimization.
  • Knowledge of Power BI Data Governance and Data Quality frameworks.
  • Certifications such as DP-203: Azure Data Engineer Associate or equivalent.

Location: PAN India
Start Date: Immediate
Work Mode: WFO
Language Requirement: English (Excellent written and verbal skills)

Form of employment: Full-time until further notice we apply 6 months probationary employment.

We interview candidates on an ongoing basis do not wait to submit your application.


Company Description We are a consulting company with a bunch of technology-interested and happy people! We love technology we love design and we love quality. Our diversity makes us unique and creates an inclusive and welcoming workplace where each individual is highly valued. With us each individua...
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Key Skills

  • Apache Hive
  • S3
  • Hadoop
  • Redshift
  • Spark
  • AWS
  • Apache Pig
  • NoSQL
  • Big Data
  • Data Warehouse
  • Kafka
  • Scala