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Sr. Data Architect (Databricks)

Posted 2024-10-24

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💎 Seniority level: Senior, 8+ years in Data Engineering; 2+ years at principal/data architect level; 5+ years in SQL, Spark, or programming languages; 2+ years in Databricks

📍 Location: United States, Canada

💸 Salary: 180000 - 215000 USD per year

🔍 Industry: Performance marketing

🏢 Company: Fluent, LLC

⏳ Experience: 8+ years in Data Engineering; 2+ years at principal/data architect level; 5+ years in SQL, Spark, or programming languages; 2+ years in Databricks

🪄 Skills: SQLMachine LearningData engineeringData scienceSparkCollaboration

Requirements:
  • Bachelor's or Master's degree in computer science.
  • 8+ years of industry experience in Data Engineering.
  • 2+ years of experience at principal/data architect level.
  • 5+ years of experience in SQL, Spark, or other programming languages.
  • 2+ years of experience with Databricks environment.
  • Familiarity with real-time ML systems within Databricks is beneficial.
Responsibilities:
  • Collaborate closely with product managers and engineers to understand business workflows and architect data solutions.
  • Model enterprise business lines with robust documentation.
  • Develop, deploy, and manage scalable data pipelines on Databricks.
  • Investigate Databricks capabilities for real-time processing and streaming.
  • Contribute to the quality of the code base with data observability and standards.
  • Mentor Junior Data Engineers and share knowledge through tech talks.
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🔥 Sr. Data Architect (Databricks)
Posted 2024-10-24

📍 Canada, United States

🧭 Full-Time

💸 180000 - 215000 USD per year

🔍 Performance marketing

🏢 Company: Fluent, LLC

  • Bachelors or Masters degree in computer science.
  • 8+ years of industry experience in Data Engineering.
  • 2+ years of experience at the principal/data architect level leading data modeling.
  • 5+ years of experience in SQL, Spark, and/or other programming languages.
  • 2+ years of experience with the Databricks environment.
  • Familiarity with real-time ML systems within Databricks is a plus.

  • Collaborate closely with product managers and engineers to understand business needs and architect data solutions.
  • Model enterprise business lines with comprehensive documentation including gold tables and pipeline flow.
  • Evaluate and recommend appropriate tools and methodologies for data modeling.
  • Develop and manage scalable data pipelines on Databricks, ensuring integration with Databricks Feature Store.
  • Implement real-time data processing and streaming capabilities using Databricks.
  • Contribute to the maintenance of a high-quality code base and best practices.
  • Partner with data science teams to translate data requirements into models.
  • Mentor junior data engineers and share knowledge through presentations and discussions.

SQLMachine LearningData engineeringData scienceSparkCollaboration

Posted 2024-10-24
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