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Fresher
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Job Description

In this role, you will design and develop scalable ETL/ELT pipelines using Databricks and Snowflake. You will be responsible for architecting data lakehouse solutions following Medallion architecture and implementing Lambda patterns for batch and real-time processing. The ideal candidate will build and maintain a single source of truth across enterprise platforms while optimizing data models and query performance. You will collaborate with cross-functional teams to translate business requirements into reliable technical solutions.

Required Skills And Qualifications

  • Proficiency in designing and developing ETL/ELT pipelines using Databricks (PySpark/Spark SQL) and Snowflake
  • Experience architecting data lakehouse solutions (Bronze, Silver, Gold layers)
  • Ability to implement Lambda architecture patterns for batch and real-time data processing
  • Skilled in developing data ingestion frameworks from databases, APIs, and streaming platforms
  • Experience with orchestration tools such as Airflow, ADF, or Databricks Workflows
  • Knowledge of CI/CD practices for data pipelines and infrastructure-as-code
  • Familiarity with data quality frameworks and pipeline monitoring.

Databricks Engineer,Snowflake,Azure,ETL/ELT,APIs

  • Experience with Delta Live Tables (DLT) or Unity Catalog
  • Knowledge of Informatica, Streamsets, or other industry-standard ETL tools
  • Familiarity with data governance and cataloging tools
  • Understanding of security and compliance standards in data engineering

More Info

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Key Skills

Data lakehouse solutions

Cataloging tools

Delta Live Tables (DLT)

Infrastructure-as-code

Streaming platforms

Data ingestion frameworks

Streamsets

Medallion architecture

Databricks Workflows

Unity Catalog

Data quality frameworks

Security and compliance standards

Lambda architecture patterns

CI/CD practices

Pipeline monitoring

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