Databricks Data Engineer | Azure | PySpark

Tiger Analytics; Hyderabad, Chennai District, Bengaluru; Hybrid; INR 900,000 - 1,300,000; Full time

Job summary

Tiger Analytics is hiring Databricks Data Engineers to build scalable data platforms on Azure. You will craft ETL/ELT pipelines, ingest and transform data, and deploy Delta Lake-based Lakehouse architectures.

Key focus areas include performance tuning of Spark jobs, streaming/batch data processing, and collaboration with data-focused teams to drive data-driven decisions.

Qualifications

• Design and develop scalable ETL/ELT pipelines using Azure Databricks.
• Build data ingestion and transformation frameworks for batch and streaming data.
• Develop data pipelines using PySpark, Azure Data Factory, and ADLS Gen2.
• Implement Delta Lake and Lakehouse architecture.
• Optimize Spark jobs for performance and scalability.

Responsibilities

• Design and develop scalable ETL/ELT pipelines using Azure Databricks.
• Build data ingestion and transformation frameworks for batch and streaming data.
• Develop data pipelines using PySpark, Azure Data Factory, and ADLS Gen2.
• Implement Delta Lake and Lakehouse architecture.
• Optimize Spark jobs for performance and scalability.
• Build logging, monitoring, and exception handling frameworks.
• Collaborate with Data Architects, Data Scientists, and Business teams.

Skills

Azure Databricks

PySpark

Python

SQL

Azure Data Factory

ADLS Gen2

Delta Lake

Spark SQL

ETL/ELT Development

Data Engineering

Tools

Azure Databricks

PySpark

Python

SQL

Azure Data Factory

ADLS Gen2

Delta Lake

Spark SQL

ETL/ELT

Data Engineering

Job description

Role & responsibilities

Job Description

Tiger Analytics is a global AI and Analytics company helping Fortune 1000 organizations build data-driven solutions using modern cloud technologies.

We are looking for skilled Databricks Data Engineers with strong expertise in Azure Data Engineering to build scalable, high-performance data platforms and pipelines.

Key Responsibilities

• Design and develop scalable ETL/ELT pipelines using Azure Databricks.
• Build data ingestion and transformation frameworks for batch and streaming data.
• Develop data pipelines using PySpark, Azure Data Factory, and ADLS Gen2.
• Implement Delta Lake and Lakehouse architecture.
• Optimize Spark jobs for performance and scalability.
• Build logging, monitoring, and exception handling frameworks.
• Collaborate with Data Architects, Data Scientists, and Business teams.

Required Skills

• Azure Databricks
• PySpark
• Python
• SQL
• Azure Data Factory (ADF)
• Azure Data Lake Storage (ADLS Gen2)
• Delta Lake
• Spark SQL
• ETL/ELT Development
• Data Engineering

Preferred Skills

• Azure Synapse Analytics
• Unity Catalog
• Delta Live Tables (DLT)
• Kafka/Event Hubs
• Azure DevOps
• CI/CD
• Databricks Workflows

Experience
46 Years

Employment Type
Full-Time