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Databricks Architect

Posted 8 days agoViewed

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💎 Seniority level: Senior, 12+ years

📍 Location: United States

🏢 Company: Tiger Analytics👥 1001-5000AdvertisingConsultingBig DataNewsMachine LearningAnalytics

⏳ Experience: 12+ years

Requirements:
  • 12+ years of experience in Architecture, design and data engineering development of large-scale data ecosystems.
  • Good exposure to AWS.
  • Experience with hadoop environment.
  • Databricks platform knowledge, Unity Catalog migration implementation exposure, Spark Streaming pipeline design exposure
Responsibilities:
  • Design and architect scalable and secure Databricks solutions platform, optimizing performance, cost, and reliability.
  • Help reduce consumption, and improve performance issues.
  • Implement DevOps process on the Databricks platform , harmonized and curation pipelines across all the programs.
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  • Solid experience working as a data engineer or related roles (8+ years)
  • Very good knowledge of the DataBricks platform and Apache Spark
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Posted 29 days ago
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📍 United States

🧭 Full-Time

🔍 B2B software and professional services

  • 7+ years’ experience in data engineering or software development, focusing on data architecture.
  • Extensive experience (3-5+ years) with Databricks and the Medallion Architecture.
  • Expertise in Python, including developing production-grade data pipelines and reusable automation scripts.
  • Proficiency in PySpark and SQL with experience integrating data sources with Databricks.
  • Expertise in cloud platform services (AWS, Azure, GCP) and their data storage solutions.
  • In-depth experience with Delta Lake for ACID transactions and data processing.
  • Strong understanding of data pipelines and transformation workflows.
  • Experience building automation tools or reusable scripts.
  • Knowledge of Alteryx and Tableau integration is a plus.
  • Design and implement scalable, high-performance data architectures using Databricks and the Medallion Architecture.
  • Lead requirement-gathering sessions with clients and internal teams to understand business needs and define best practices for solutions including data workflows.
  • Collaborate with cloud platform teams for data storage optimization.
  • Translate complex data processes into optimized Databricks workflows using PySpark and SQL.
  • Develop reusable automation scripts for workflow migrations.
  • Provide hands-on development and troubleshooting support.
  • Partner with teams to establish data governance frameworks and best practices.
  • Deliver training and documentation to enhance data literacy.

AWSPythonSQLAzureData engineering

Posted 5 months ago
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