AWS Databricks Engineer

Hello All,

ZettaMine!!!

Role: Databricks Data Engineer

Experience: 8+ Years

Location: Hyderabad, PAN INDIA

Notice Period: Immediate Joiners

Primary Skills: Databricks | Apache Spark | PySpark | Spark SQL | Python | Scala | Delta Lake | ETL/ELT Pipelines | Batch & Real-Time Data Processing | AWS | Data Modeling (Star/Snowflake) | Power BI | Performance Optimization | MLflow | CI/CD | Git | Data Governance | Agile Scrum

Hiring for one of the Big 4's Clients

We are looking for Immediate to 15 Days Joiners

Databricks Data Engineer

Key Responsibilities :

• Design, develop, and optimize large-scale data processing solutions using

  Databricks

  .
• Build and maintain robust

  ETL/ELT pipelines

  for batch and near real-time data ingestion.
• Develop data transformation workflows using

  Apache Spark, PySpark, Spark SQL, Python, and Scala

  .
• Implement and manage

  Delta Lake

  features including ACID transactions, schema evolution, and performance optimization.
• Design and develop analytical and dimensional data models using

  Star Schema

  and

  Snowflake Schema

  methodologies.
• Integrate and manage data stored in

  AWS cloud storage platforms

  .
• Collaborate with business stakeholders, data architects, BI developers, and data scientists to deliver end-to-end data solutions.
• Ensure adherence to coding standards, documentation requirements, and data engineering best practices.
• Troubleshoot and optimize data pipelines for performance, scalability, reliability, and cost efficiency.
• Participate in code reviews, technical discussions, and Agile ceremonies.

Roles & Responsibilities :

• Develop scalable data engineering solutions on the Databricks platform.
• Build and optimize data ingestion frameworks and transformation pipelines.
• Maintain high-performance data lakes using Delta Lake architecture.
• Create reusable frameworks, notebooks, and automation components.
• Support reporting and analytics initiatives through Power BI integration.
• Implement CI/CD best practices for Databricks deployments.
• Collaborate with cross-functional teams to deliver business-focused solutions.
• Ensure compliance with enterprise data governance and security standards.
• Monitor, troubleshoot, and enhance the reliability of production data platforms.
• Support ML and AI initiatives through feature engineering and model data preparation.

praneeth.n@zettamine.com

Thanks& Regards,

Praneeth