
Databricks Data Engineer 6+ years
4 days ago
Position Overview
We are looking for an experienced Databricks Data Engineer with 6+ years of expertise in building and managing large-scale data platforms. The ideal candidate will have strong hands-on experience with Databricks, Spark, and Cloud Data Engineering practices. This role involves designing, developing, and optimizing data pipelines, enabling advanced analytics, and ensuring scalable and efficient data solutions.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines on Databricks.
- Work with Apache Spark, Delta Lake, and SQL to transform and optimize large datasets.
- Collaborate with data scientists, analysts, and business stakeholders to deliver reliable data solutions.
- Implement best practices for data security, governance, and compliance.
- Support migration, integration, and modernization of data platforms to cloud environments.
- Troubleshoot performance bottlenecks and ensure high availability of data pipelines.
- Work in an Agile/DevOps environment, supporting CI/CD pipelines and automation.
Skills Required
- Strong hands-on experience in Databricks and Apache Spark.
- Proficiency in SQL, Python, or Scala.
- Experience with ETL development, data modeling, and data warehousing concepts.
- Knowledge of cloud platforms (Azure, AWS, or GCP) with emphasis on data services.
- Familiarity with Delta Lake, MLflow, and data pipeline orchestration tools (Airflow, ADF, etc.).
- Strong understanding of data governance, performance tuning, and optimization.
Preferred Skills
- Experience in Azure Databricks with integration of Azure Data Lake, Synapse, or Data Factory.
- Knowledge of machine learning workflows within Databricks.
- Exposure to DevOps practices and CI/CD for data engineering.
- Professional certifications in Databricks or cloud platforms (Azure, AWS, GCP).
Job Types: Full-time, Permanent
Pay: ₹469, ₹1,817,548.30 per year
Experience:
- Databricks data engineer: 6 years (Preferred)
- ETL: 6 years (Preferred)
- Cloud computing: 6 years (Preferred)
- DevOps: 6 years (Preferred)
Work Location: In person
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