Databricks Data Engineering Specialist

2 weeks ago

Bikaner, Rajasthan, India beBeeDatabricks Full time

**Job Description:**

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Design and implement scalable, secure, and efficient Databricks solutions that meet client requirements.

Our boutique consulting firm specializes in data and AI, with deep expertise in the Databricks ecosystem. We help clients build scalable data platforms and AI solutions that drive real business impact.

Our team empowers clients to harness the full potential of their data, unlocking significant competitive advantages and fostering innovation.

Key Responsibilities:

  1. Develop data pipelines, architect data lakes, and implement data warehousing solutions using Databricks.
  2. Collaborate with data scientists and analysts to develop and deploy machine learning models and analytics solutions on Databricks.
  3. Optimize Databricks cluster performance, ensuring efficient resource utilization and cost-effectiveness.
  4. Implement Databricks security features, ensure data governance, and maintain compliance with industry regulations.
  5. Work closely with clients to understand their business requirements, provide technical guidance, and deliver high-quality Databricks solutions.
  6. Stay up-to-date with the latest Databricks features, best practices, and industry trends, and share knowledge with the team.

Requirements:

  1. 5+ years of experience working with Databricks, including platform architecture, data engineering, and data analytics.
  2. Proficiency in languages such as Python, Scala, or Java, and experience with Databricks APIs, Spark, and Delta Lake.
  3. Strong background in data engineering, including data warehousing, ETL, and data governance.
  4. Proven experience leading technical teams, mentoring junior engineers, and driving technical initiatives.
  5. Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal stakeholders.

Good to Have:

  • Databricks Certified Professional or similar certifications.
  • Experience working with cloud platforms such as AWS, Azure, or GCP.
  • Knowledge of machine learning concepts and experience with popular ML libraries.

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