Databricks Engineering Professional

4 days ago

Coimbatore, Tamil Nadu, India beBeeData Full time ₹ 18,00,000 - ₹ 25,00,000
Job Description

We are seeking a seasoned Databricks Administrator to join our team. As a key member of our data engineering department, you will be responsible for designing, deploying, and managing large-scale Databricks clusters.

Responsibilities include:

  1. Designing and implementing high-performance Databricks cluster architectures;
  2. Deploying and configuring Databricks notebooks, libraries, and job scheduling;
  3. Optimizing Spark performance, caching, and tuning for complex data workloads;
  4. Developing and maintaining automation scripts using Terraform, ARM templates, or CloudFormation;
  5. Collaborating with cross-functional teams to design and implement scalable data pipelines;
  6. Maintaining and improving existing infrastructure, ensuring high availability and reliability.
Required Skills and Qualifications

To succeed in this role, you must have:

  1. At least 7 years of experience as a Databricks Administrator or in a similar position;
  2. Strong knowledge of Azure/AWS Databricks and cloud computing platforms;
  3. Hands-on experience with Databricks clusters, notebooks, libraries, and job scheduling;
  4. Expertise in Spark optimization, data caching, and performance tuning;
  5. Proficiency in Python, Scala, or SQL for data processing;
  6. Experience with Terraform, ARM templates, or CloudFormation for infrastructure automation;
  7. Familiarity with Git, DevOps, and CI/CD pipelines.
Benefits

This is an exciting opportunity to join a dynamic team and take your career to the next level. You will enjoy:

  1. A competitive salary and benefits package;
  2. Opportunities for professional growth and development;
  3. Collaborative and inclusive work environment;
  4. Flexible working arrangements and remote work options.
Preferred Qualifications

We welcome candidates with:

  1. Databricks certifications (e.g., Databricks Certified Associate/Professional);
  2. Experience in Delta Lake, Unity Catalog, and MLflow;
  3. Knowledge of Kubernetes, Docker, and containerized workloads;
  4. Experience with big data ecosystems (Hadoop, Apache Airflow, Kafka, etc.).

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