Senior Data Processing Specialist

5 days ago

Kolkata, West Bengal, India beBeeDataEngineer Full time ₹ 15,00,000 - ₹ 28,00,000

Azure Data Bricks Engineer Position

As a highly skilled and experienced data engineer, you will play a key role in designing, developing, and maintaining robust data processing pipelines and analytics solutions using Databricks.

This challenging position involves working closely with our architecture and engineering teams to architect scalable and efficient data models and storage solutions tailored for the Databricks environment. You will be responsible for migrating existing solutions to Databricks, ensuring seamless integration and optimal performance.

To excel in this role, you must have a solid understanding of distributed computing principles and big data frameworks like Apache Spark. Proficiency in Python, Scala, or SQL is essential, as well as experience with major cloud platforms (AWS, Azure, or GCP) and their respective data services.

A bachelor's or master's degree in Computer Science, Engineering, or a related technical discipline is required, along with at least 5 years of overall experience in data engineering, with a minimum of 2 years focused on Databricks. Strong analytical and problem-solving skills are crucial, as well as effective communication and collaboration skills within cross-functional teams.

  • Key Responsibilities:
  • Data Pipeline Development: Design and develop robust data processing pipelines and analytics solutions using Databricks.
  • Architecture & Modeling: Architect scalable and efficient data models and storage solutions tailored for the Databricks environment.
  • Migration & Integration: Collaborate with architecture and engineering teams to migrate existing solutions to Databricks.
  • Performance Optimization: Tune and optimize Databricks clusters and job performance to meet SLAs and evolving business needs.
  • Governance & Compliance: Implement best practices for data governance, security, and compliance on the Databricks platform.
  • Mentorship: Guide and mentor junior engineers, offering technical support and best practice recommendations.
  • Innovation & Learning: Stay informed about emerging data engineering trends and new features in Databricks and related technologies.

Required Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline.
  • 5 to 8 years of overall experience in data engineering, with a minimum of 2 years focused on Databricks.
  • Hands-on proficiency in Python, Scala, or SQL.
  • Solid understanding of distributed computing principles and big data frameworks like Apache Spark.
  • Experience with major cloud platforms (AWS, Azure, or GCP) and their respective data services.
  • Demonstrated ability to build scalable and reliable data solutions in dynamic environments.
  • Strong analytical and problem-solving skills with high attention to detail.
  • Effective communication and collaboration skills within cross-functional teams.

Preferred Qualifications:

  • Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
  • Understanding of DevOps practices for automating deployments and monitoring data pipelines.

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