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Algotale-Delphi( Azure Databricks Developer)

Nexthire · Pune, Bangalore, IN

External listingfull-time5 months ago

About The Role

Job Title

Azure Databricks Developer

Company

Algotale

Location

Bangalore / Pune, India

Experience

6+ Years

Job Summary

Algotale is seeking a skilled

Azure Databricks Developer

to design, develop, and optimize scalable data solutions on the Azure cloud platform. The ideal candidate will have strong expertise in big data processing, ETL pipelines, and distributed computing using Databricks.

Key Responsibilities

Develop and maintain scalable data pipelines using

Azure Databricks

Design and implement ETL/ELT workflows using

PySpark / Spark SQL

Work with

Azure Data Lake Storage (ADLS)

,

Azure Synapse

  • , and other Azure services
  • Optimize performance of Spark jobs and data workflows
  • Collaborate with data engineers, analysts, and business stakeholders
  • Implement data quality checks, monitoring, and logging
  • Ensure data security and governance best practices
  • Troubleshoot and resolve data pipeline issues

Required Skills & Qualifications

Strong experience with

Azure Databricks

Proficiency in

Python (PySpark)

and

SQL

Experience with

Apache Spark

  • and distributed data processing
  • Hands-on experience with
  • Azure ecosystem

Azure Data Factory (ADF)

Azure Data Lake Storage (ADLS)

Azure Synapse Analytics

  • Understanding of data warehousing concepts
  • Experience in building batch and streaming pipelines
  • Familiarity with version control tools like

Git

Preferred Skills

Experience with

Delta Lake

Knowledge of

CI/CD pipelines (Azure DevOps)

Exposure to

Kafka / Event Hubs

  • for streaming
  • Understanding of data modeling techniques
  • Certifications in Azure (e.g., DP-203) are a plus

Soft Skills

  • Strong problem-solving and analytical skills
  • Good communication and collaboration abilities
  • Ability to work in an agile environment
  • Why Join Algotale?
  • Opportunity to work on cutting-edge cloud data technologies
  • Collaborative and growth-oriented environment
  • Exposure to large-scale data engineering projects

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