10 - 20 years

3 - 6 Lacs

Posted:1 month ago| Platform: Foundit logo

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Skills Required

Work Mode

On-site

Job Type

Full Time

Job Description

Key Responsibilities

  • Lead the design, architecture, and implementation of Azure Databricks solutions for data processing and analytics.
  • Develop and optimize ETL/ELT pipelines using Apache Spark, Python (PySpark), Scala, and SQL.
  • Work closely with data engineers, data scientists, and business stakeholders to ensure efficient data workflows.
  • Implement data governance, security, and compliance best practices in Databricks and Azure Data Lake.
  • Optimize performance tuning, cost management, and scalability of Databricks workloads.
  • Automate CI/CD pipelines for Databricks notebooks using DevOps tools like Azure DevOps, Terraform, or GitHub Actions.
  • Troubleshoot and resolve issues related to big data processing, Spark jobs, and cloud storage.
  • Stay updated with Azure and Databricks best practices and mentor junior team members.
  • Required Skills & Experience:


10+ years of experience in data engineering, big data, or cloud-based data solutions.

  • Strong hands-on experience with Azure Databricks, Apache Spark, and Delta Lake.
  • Expertise in Python (PySpark), Scala, SQL, and data transformation techniques.
  • Deep understanding of Azure Data Services (Azure Data Lake, Azure Synapse, Azure Data Factory, etc.).
  • Experience with data modeling, ETL/ELT design, and distributed data processing.
  • Proficiency in DevOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and version control (Git).
  • Familiarity with MLflow, Unity Catalog, and Databricks SQL is a plus.
  • Strong analytical, problem-solving, and communication skills.


Preferred Qualifications

  • Databricks certifications (e.g., Databricks Certified Data Engineer Associate/Professional).
  • Experience with containerization (Docker, Kubernetes) and orchestration tools.
  • Knowledge of real-time data streaming using Kafka, Event Hubs, or similar technologies.
  • Exposure to Machine Learning (ML) workflows in Databricks is a plus.

  • Competitive Salary
  • Performance based Variable Pay
  • Health, Vision, Dental, and Life Insurance
  • Comprehensive Employee Wellness Plan
  • Retirement plan
  • Paid Holidays and Vacation Time Accrual
  • Encouraging and highly energetic environment
  • Personal and Professional Growth Opportunities

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