Senior Data Engineer

Position: Senior Data Engineer

Location:

Experience Required:

Job Type:

Data Engineer with strong expertise in Microsoft Azure

Key Responsibilities:

• Design and implement robust data pipelines using Azure Data Factory, Azure Data Lake, and other Azure services.
• Develop and optimize large-scale data processing using

  Databricks and PySpark

  .
• Work with both

  relational (SQL)

  and

  NoSQL databases

  to manage structured and semi-structured data.
• Write clean, maintainable code using

  Python and/or Scala

  .
• Collaborate with cross-functional teams including data scientists, analysts, and DevOps engineers.

Required Skills:

• 7–11 years of professional experience as a Data Engineer.
• Deep hands-on expertise with

  Azure Data Services

  .
• Solid experience with

  Databricks

  and

  PySpark

  .
• Proficiency in SQL and NoSQL databases.
• Strong background in

  Python

  ,

  Scala

  , and object-oriented programming.

Data Engineer with GCP and Databricks experience

Key Responsibilities:

• Build, maintain, and optimize scalable data pipelines using

  Databricks

  and

  Google Cloud (BigQuery, Cloud Storage, etc.)

  .
• Collaborate with analytics and data science teams to enable data-driven decision-making.
• Perform

  exploratory data analysis (EDA)

  to understand and prepare data for modeling and business use.
• Ensure best practices in data modeling, governance, and lifecycle management.

Required Skills:

• 7–11 years of professional experience in data engineering.
• Expert-level proficiency in

  Databricks

  ,

  BigQuery

  , and

  Python

  .
• Strong command over

  SQL

  with large datasets.
• Exposure to

  data science concepts

  and

  EDA

  methodologies.
• Familiarity with CI/CD processes and version control systems.