Data Engineer-Databricks (Face-to-face Interview on 31st)

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Data Engineer

Key Responsibilities

• Design, develop, and maintain

  scalable data pipelines

  using

  Azure Databricks

• Build and optimize

  ETL/ELT workflows

  using

  PySpark

• Ingest data from multiple sources and perform

  data transformation and cleansing

• Write optimized

  Spark SQL and SQL queries

  for data processing and analytics
• Perform

  data validation, reconciliation, and quality checks

• Optimize Spark jobs for

  performance, scalability, and cost efficiency

• Collaborate with data analysts, BI teams, and business stakeholders to understand data needs
• Implement

  best practices

  for coding standards, testing, and deployment
• Troubleshoot and resolve

  pipeline failures and production issues

• Participate in

  code reviews, design discussions, and agile ceremonies

• Provide support for production deployments and enhancements

Mandatory Skills (Must-Have)

• Azure Databricks (ADB)

• PySpark

• Python

• SQL

Preferred / Good-to-Have Skills

• Experience with

  Azure Data Factory (ADF)

  and

  Azure Data Lake (ADLS)

• Strong understanding of

  Big Data concepts and distributed processing

• Knowledge of

  data warehousing and data modeling

• Experience in handling

  structured and semi-structured data

• Familiarity with

  Unix/Linux commands

• Experience working in

  Agile/Scrum environments

Experience Requirements

• 5 to 10 years

  of experience in

  Data Engineering / Big Data Engineering

• Candidates with

  9+ years

  should have :
• Technical ownership of data pipelines

• Lead Experience

• Driving design and best practices

Education

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or related discipline

Soft Skills

• Strong analytical and problem-solving skills
• Good communication and stakeholder interaction skills
• Ability to work independently and in cross-functional teams
• Adaptability to fast-paced project environments