Senior Cloud Data Engineer

5 hours ago

Kolkata, West Bengal, India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Job Title: Databricks Engineer

We are seeking an experienced Databricks engineer to join our team. As a key member of our data engineering group, you will be responsible for designing, developing, and maintaining data pipelines and ETL processes on Databricks.

Key Responsibilities
  • Data Pipeline Development: Design, develop, and maintain data pipelines and ETL processes on Databricks to ensure efficient data processing and storage.
  • Data Architecture: Lead the architecture and implementation of scalable, secure, and high-performance data solutions using Databricks and other cloud-based technologies.
  • Collaboration: Collaborate with business stakeholders, data scientists, and analysts to gather requirements and deliver actionable data solutions that meet their needs.
  • Workflow Optimization: Optimize data workflows for performance, cost-efficiency, and reliability to ensure high-quality data delivery.
  • Data Integration: Integrate data from multiple structured and unstructured sources into Delta Lake and cloud data warehouses to create a unified data environment.
  • Best Practices: Implement best practices in data governance, security, and quality management to ensure compliance and data integrity.
  • Tech Leadership: Mentor junior engineers and provide technical leadership in data engineering best practices to support team growth and development.
  • Troubleshooting: Troubleshoot and resolve issues in data pipelines, ensuring high data availability and integrity.
Required Skills & Experience
  • Data Engineering Expertise: 7+ years of experience in Data Engineering, with a strong focus on data pipeline development, data architecture, and data integration.
  • Databricks Mastery: Proven Subject Matter Expertise in Databricks (including Databricks SQL, Delta Lake, and MLflow), with a strong understanding of its features and capabilities.
  • Programming Skills: Strong experience with PySpark, Spark SQL, and Scala, with a solid understanding of programming concepts and principles.
  • Cloud Platforms: Hands-on experience with cloud platforms (Azure preferred; AWS/GCP a plus), with a strong understanding of cloud-based data architectures.
  • Data Modeling: Proficiency in data modeling, ETL development, and data warehousing concepts, with a strong focus on data quality and integrity.
  • Big Data Ecosystems: Solid understanding of big data ecosystems (Hadoop, Kafka, etc.), with a strong focus on data processing and storage.
  • SQL Development: Strong SQL development skills with a focus on performance tuning, with a strong understanding of database design and optimization.
  • CI/CD Pipelines: Experience in implementing CI/CD pipelines for data solutions, with a strong focus on automation and continuous improvement.

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