Senior Data Architect

1 day ago

Jodhpur, Rajasthan, India beBeeDataArchitect Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Job Title: Data Architect

We are seeking an experienced Data Architect to design and implement scalable data architectures following Medallion Architecture and best practices.

  • Develop and optimize ETL/ELT pipelines using Azure Data Factory (ADF), Databricks, and Synapse Analytics.
  • Design and implement scalable data architectures.
  • Perform data ingestion, transformation, and orchestration across structured and unstructured datasets.

The ideal candidate will have strong experience in Azure Data Engineering with Data Factory, Synapse, Fabric, and Databricks.

  • Expertise in SQL, T-SQL, and Python for data processing and transformation.
  • Hands-on experience with PySpark for big data processing.
  • Experience in designing ETL/ELT pipelines and working with large datasets.

Key Responsibilities:

  1. Develop and optimize ETL/ELT pipelines.
  2. Design and implement scalable data architectures.
  3. Perform data ingestion, transformation, and orchestration.
  4. Write and optimize SQL queries.
  5. Implement CI/CD pipelines for data workflows.
  6. Collaborate with stakeholders to understand data requirements.
  7. Ensure data governance, security, and compliance.
  8. Monitor and troubleshoot data pipelines.
  9. Stay updated with the latest technologies.
  10. Resolve issues through exhaustive systematic analysis.
  11. Carry out POCs to ensure suggested design meets requirements.

Required Skills:

  • Azure Data Engineering with Data Factory, Synapse, Fabric, Databricks.
  • SQL, T-SQL, and Python for data processing and transformation.
  • PySpark for big data processing.
  • ETL/ELT pipelines and working with large datasets.
  • Azure Data Lake (ADLS) Gen2 for data storage and processing.
  • CI/CD and DevOps knowledge, including Azure DevOps, Git, and automated deployments.
  • Data modeling, data warehousing, and schema design principles.

Desirable Skills:

  • New Age Technologies like Low Code, No Code, DevOps.
  • Data Governance and Security best practices.
  • Real-time data processing using Kafka, Event Hub, or Stream Analytics.
  • DataOps methodologies and best practices.
  • APIs, REST services, and integrating third-party data sources.

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