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Cloudxtreme

Azure Databricks Lead - Scala PySpark

Cloudxtreme

Hyderabad, Telangana, India · На постоянной основе

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Опыт
Любой
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Открытия
1
Опубликовано
3 часа назад
Режим работы
В офисе
Образование
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Критерии отбора
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Где вы будете работать

Описание работы

Role overview

This position is for an Azure Databricks Lead who will guide data platform modernization efforts in Hyderabad/Bengaluru. The role centers on building scalable data solutions, leading migration work from Hadoop to Azure, and helping teams use data effectively across multiple portfolios.

Core responsibilities

  • Design, develop, and maintain robust ETL pipelines that move data from multiple sources into data lakes and data warehouses.
  • Lead the transition from Hadoop-based systems to Azure and define how data will be used across different portfolios.
  • Create and implement data models that support efficient storage, fast retrieval, and effective analytics for varied data volumes and types.
  • Bring together data from databases, APIs, streaming tools, and external systems while maintaining consistency and accuracy.
  • Clean, transform, and enrich raw data so it is reliable and ready for reporting, analysis, and downstream consumption.
  • Build and maintain data warehouse or data lake solutions capable of managing large structured and unstructured datasets.
  • Apply governance and security practices to safeguard sensitive information and support compliance requirements such as GDPR and CCPA.
  • Track and improve data processing and query performance by identifying bottlenecks and optimizing workloads.
  • Work closely with data analysts and data scientists to understand their needs and deliver well-organized, dependable datasets.

Technical skills and experience

  • Strong programming and scripting ability in Python, SQL, or Scala for automation, ETL, and data handling.
  • Hands-on experience with Azure cloud services, Azure Databricks, SQL, Spark, and either Scala or Python.
  • Working knowledge of Jira, GitHub, and DevOps-related tools and practices.
  • Exposure to data integration and ETL frameworks such as Kafka, Spark, Airflow, or Talend.
  • Understanding of data modeling, dimensional modeling, and database schema design.
  • Experience with big data ecosystems such as Hadoop, Hive, HBase, or Cassandra.
  • Familiarity with cloud-based data storage, processing, and analytics platforms.
  • Knowledge of data governance, data protection, and regulatory compliance practices.
  • Strong analytical thinking and troubleshooting skills with attention to detail.
  • Clear communication and collaboration skills for working with technical and non-technical stakeholders.

Eligibility

Any graduate may apply for this opportunity.

Additional information

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