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Databricks Data Engineer (Job No 941)

For Gbm Is A Leading End-To-End Digital Solutions Provider.

5 - 10 Years

Full Time

Immediate

Up to 40 LPA

1 Position(s)

Remote/Work From Home (Wfh)

5 - 10 Years

Full Time

Immediate

Up to 40 LPA

1 Position(s)

Remote/Work From Home (Wfh)

Job Skills

Job Description

Key Responsibilities:

  1. Develop & Optimize ETL Pipelines:
    • Build robust and scalable data pipelines using ADF, Databricks, and Python for data ingestion, transformation, and loading.
  2. Data Modeling & Systematic Layer Modeling:
    • Design logical, physical, and systematic data models for structured and unstructured data.
  3. Integrate SAP IS-Auto:
    • Extract, transform, and load data from SAP IS-Auto into Azure-based data platforms.
  4. Database Management:
    • Develop and optimize SQL queries, stored procedures, and indexing strategies to enhance performance.
  5. Big Data Processing:
    • Work with Azure Databricks for distributed computing, Spark for large-scale processing, and Delta Lake for optimized storage.
  6. Data Quality & Governance:
    • Implement data validation, lineage tracking, and security measures for high-quality, compliant data.
  7. Collaboration:
    • Work closely with business analysts, data scientists, and DevOps teams to ensure data availability and usability.
  8. Testing and Debugging:
    • Write unit tests and perform debugging to ensure the Implementation is robust and error-free.
    • Conduct performance optimization and security audits.

Required Skills and Qualifications:

  1. Azure Cloud Expertise:
    • Strong experience in Azure Data Factory (ADF), Databricks, and Azure Synapse.
  2. Programming:
    • Proficiency in Python for data processing, automation, and scripting.
  3. SQL & Database Skills:
    • Advanced knowledge of SQL, T-SQL, or PL/SQL for data manipulation.
  4. SAP IS-Auto Data Handling:
    • Experience integrating SAP IS-Auto as a data source into data pipelines.
  5. Data Modeling:
    • Hands-on experience in dimensional modeling, systematic layer modeling, and entity-relationship modeling.
  6. Big Data Frameworks:
    • Strong understanding of Apache Spark, Delta Lake, and distributed computing.
  7. Performance Optimization:
    • Expertise in query optimization, indexing, and performance tuning.
  8. Data Governance & Security:
    • Knowledge of RBAC, encryption, and data privacy standards.

Preferred Qualifications:

  1. Experience with CI/CD for data pipelines using Azure DevOps.
  2. Knowledge of Kafka/Event Hub for real-time data processing.
  3. Experience with Power BI/Tableau for data visualization (not mandatory but a plus).