Databricks Architect

Genpact Ltd.

Pune District, Bengaluru, Delhi

Ibrido

INR 1.800.000 - 3.000.000

Tempo pieno

8 giorni fa

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Curriculum e lettera di presentazione personalizzati, pronti da inviare.

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Descrizione del lavoro

Genpact Ltd. is seeking a Databricks Architect to design and implement end-to-end data pipelines, blending batch and streaming processes across Azure/AWS/GCP.

The role emphasizes deep Data Engineering expertise, Unity Catalog governance, and Databricks Lakehouse implementation in enterprise environments. You will collaborate with senior architects and engineers to deliver scalable, cost-efficient data platforms, including Delta Lake, DBT integrations, and robust testing.

Competenze

  • Must have experience in Data Engineering domain.
  • Must have implemented at least 4 project end-to-end in Databricks.
  • Must have skills: Azure data factory, Azure data bricks, Python and Pyspark.
  • Expert with database technologies and ETL tools.
  • Hands-on experience on designing and developing scripts for custom ETL processes and automation in Azure data factory, Azure databricks, Python, Pyspark etc.
  • Good knowledge of AZURE, AWS, GCP Cloud platform services stack.
  • Hands-on experience on designing and developing scripts for custom ETL processes and automation in Azure data factory, Azure databricks, Delta lake, Databricks workflows orchestration, Python, Pyspark etc.
  • Good Knowledge on Unity Catalog implementation.
  • Good Knowledge on integration with other tools like DBT, other transformation tools.
  • Good knowledge on Unity Catalog integration with Snowlflake
  • Must be well versed with Databricks Lakehouse concept and its implementation in enterprise environments.
  • Must have good understanding to create complex data pipeline
  • Must have good knowledge of Data structure & algorithms.
  • Must be strong in SQL and sprak-sql.
  • Must have strong performance optimization skills to improve efficiency and reduce cost.
  • Must have worked on both Batch and streaming data pipeline.
  • Must have extensive knowledge of Spark and Hive data processing framework.
  • Must have worked on any cloud (Azure, AWS, GCP) and most common services like ADLS/S3, ADF/Lambda, CosmosDB/DynamoDB, ASB/SQS, Cloud databases.
  • Must be strong in writing unit test case and integration test
  • Must have strong communication skills and have worked on the team of size 5 plus
  • Must have great attitude towards learning new skills and upskilling the existing skills. Preferred Qualifications
  • Good to have Unity catalog and basic governance knowledge.
  • Good to have Databricks SQL Endpoint understanding.
  • Good To have CI/CD experience to build the pipeline for Databricks jobs.

Mansioni

  • Maintains close awareness of new and emerging technologies and their potential application for service offerings and products.
  • Work with architect and lead engineers for solutions to meet functional and non functional requirements.
  • Demonstrated knowledge of relevant industry trends and standards.
  • Demonstrate strong analytical and technical problem-solving skills.
  • Must have experience in Data Engineering domain.

Conoscenze

Databricks
Data Engineering
Python
Pyspark
SQL
Spark SQL
Delta Lake
Unity Catalog
Azure
AWS
GCP
DBT
CI/CD
ETL
Streaming
Batch processing

Strumenti

Azure Data Factory
Azure Databricks
Databricks Workflows
Delta Lake
Snowflake
DBT
CosmosDB
DynamoDB
S3
ADLS

Descrizione del lavoro

Role & responsibilities

In this role, the Databricks Architect is responsible for solving the real-world cutting-edge problem to meet both functional and non-functional requirements.

  • Maintains close awareness of new and emerging technologies and their potential application for service offerings and products.
  • Work with architect and lead engineers for solutions to meet functional and non functional requirements.
  • Demonstrated knowledge of relevant industry trends and standards.
  • Demonstrate strong analytical and technical problem-solving skills.
  • Must have experience in Data Engineering domain.
Preferred candidate profile
  • Must have experience in Data Engineering domain .
  • Must have implemented at least 4 project end-to-end in Databricks.
  • Must have at least experience on databricks which consists of various components as below
  • Must have skills: Azure data factory, Azure data bricks, Python and Pyspark
  • Expert with database technologies and ETL tools.
  • Hands-on experience on designing and developing scripts for custom ETL processes and automation in Azure data factory, Azure databricks, Python, Pyspark etc.
  • Good knowledge of AZURE, AWS, GCP Cloud platform services stack
  • Hands-on experience on designing and developing scripts for custom ETL processes and automation in Azure data factory, Azure databricks, Delta lake, Databricks workflows orchestration, Python, Pyspark etc.
  • Good Knowledge on Unity Catalog implementation.
  • Good Knowledge on integration with other tools like DBT, other transformation tools.
  • Good knowledge on Unity Catalog integration with Snowlflake
  • Must be well versed with Databricks Lakehouse concept and its implementation in enterprise environments.
  • Must have good understanding to create complex data pipeline
  • Must have good knowledge of Data structure & algorithms.
  • Must be strong in SQL and sprak-sql.
  • Must have strong performance optimization skills to improve efficiency and reduce cost.
  • Must have worked on both Batch and streaming data pipeline.
  • Must have extensive knowledge of Spark and Hive data processing framework.
  • Must have worked on any cloud (Azure, AWS, GCP) and most common services like ADLS/S3, ADF/Lambda, CosmosDB/DynamoDB, ASB/SQS, Cloud databases.
  • Must be strong in writing unit test case and integration test
  • Must have strong communication skills and have worked on the team of size 5 plus
  • Must have great attitude towards learning new skills and upskilling the existing skills. Preferred Qualifications
Preferred Qualifications
  • Good to have Unity catalog and basic governance knowledge.
  • Good to have Databricks SQL Endpoint understanding.
  • Good To have CI/CD experience to build the pipeline for Databricks jobs.
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