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Azure Data Engineer - PySpark

Azure Data Engineer - PySpark

Lancesoft India Pvt LtdMumbai
12 days ago
Job description

Description : LanceSoft is a global leader in providing technology and talent solutions, and we are looking for a highly skilled and experienced Azure Data Engineer to join our dynamic team.

If you thrive on building scalable, high-performance data pipelines in the cloud, we want to hear from you!

Role Details

Job Title : Azure Data Engineer

Experience : 58 years

Location : SEEPZ, Andheri, Mumbai, Maharashtra

Key Responsibilities :

As an Azure Data Engineer, you will be crucial in designing and maintaining our cutting-edge data platform.

Your primary responsibilities will include :

  • Data Pipeline Development : Design, build, and maintain robust and scalable data pipelines utilizing Azure Databricks, PySpark, and Azure Data Factory (ADF).
  • Data Transformation (ETL / ELT) : Perform complex Extract, Transform, and Load (ETL) processes from various disparate sources into Azure Data Lake Storage (ADLS) or equivalent.
  • SQL Expertise : Write, optimize, and tune advanced SQL queries, stored procedures, and complex data transformations for optimal performance.
  • Collaboration : Work closely with data scientists, business analysts, and fellow engineers to translate business requirements into efficient, high-impact data solutions.
  • Performance & Reliability : Monitor data pipeline performance, troubleshoot technical issues, and ensure solutions are reliable, scalable, and meet service level objectives (SLOs).
  • Documentation : Maintain comprehensive and clear documentation of data flows, schemas, and transformations to ensure system maintainability.

Required Technologies & Skills :

Candidates must have strong, hands-on experience with the following :

  • Cloud & ETL : Azure Data Factory (ADF), Azure Databricks.
  • Programming & Scripting : PySpark, SQL, and SSIS (SQL Server Integration Services).
  • Development Tools : Visual Studio.
  • Methodology : Understanding and experience with DevOps practices (CI / CD for data solutions)
  • (ref : hirist.tech)

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