Senior Data Engineer (Databricks & Cloud Analytics)

System One Holdings, LLC

• $112K — $135K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Information Systems, Engineering, or related field, or equivalent experience.
  • 6+ years of experience in enterprise data platforms or cloud data solutions.
  • Extensive hands-on experience with Databricks, Apache Spark, Python, SQL, and Scala.
  • Proven skills in SQL development, including optimization and performance tuning.
  • Experience with ETL/ELT solutions on cloud platforms like Azure Data Factory.
  • Familiarity with event streaming systems like Kafka.
  • Proficiency in using Git for version control.

Responsibilities

  • Design and develop enterprise data platforms and cloud analytics solutions.
  • Build scalable data pipelines using Databricks, Apache Spark, and Python.
  • Manage Databricks ecosystem components, including Delta Lake and MLflow.
  • Optimize SQL queries for improved performance.
  • Implement ETL/ELT processes utilizing Azure Data Factory.
  • Integrate applications using event streaming technologies and REST APIs.
  • Collaborate in Linux environments and utilize shell scripting.

Benefits

  • Hybrid work model with onsite and remote flexibility.
  • Opportunities for technical mentoring and leadership.
  • Participation in Agile teams with modern methodologies.
  • Access to cutting-edge technologies and tools.
  • Collaborative work environment with a focus on innovation.
Full Job Description
Job Title: Senior Data Engineer (Databricks & Cloud Analytics)
Location: Salt Lake City, Utah
Work Model: Hybrid - onsite and remote

Responsibilities
• Design, develop, and support enterprise data platforms, cloud analytics solutions, or large-scale data engineering initiatives.
• Work hands-on with Databricks, Apache Spark (PySpark), Python, SQL, and Scala to build scalable data pipelines and analytics solutions.
• Manage and implement Databricks ecosystem components, including Workspaces, Delta Lake, Unity Catalog, Delta Live Tables, Databricks SQL, MLflow, and Databricks Jobs.
• Optimize SQL queries and improve query performance through tuning and best practices.
• Design and implement ETL/ELT processes utilizing cloud platforms such as Azure Data Factory.
• Work with event streaming technologies like Apache Kafka and integrate enterprise applications via REST APIs and web services.
• Utilize Azure Data Lake Storage (ADLS Gen2) and other cloud storage solutions.
• Collaborate within Linux environments, including shell scripting and command-line utilities.
• Use source control tools like Git for collaborative development.
• Participate in Agile teams practicing Scrum, Kanban, or SAFe methodologies.
• Provide technical mentoring and leadership within data engineering teams.

Requirements
• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field or equivalent professional experience.
• At least 6 years of experience designing and supporting enterprise data platforms or cloud data solutions.
• Extensive hands-on experience with Databricks, Apache Spark, Python, SQL, and Scala.
• Proven SQL development skills, including query optimization and performance tuning.
• Experience designing ETL/ELT solutions with cloud platforms such as Azure Data Factory.
• Knowledge of Kafka or similar event streaming systems.
• Familiarity with cloud data storage (Azure Data Lake Storage or equivalents).
• Proficiency using Git for version control.
• Experience working in Linux environments and scripting.
• Preferred: Infrastructure as Code (Terraform), CI/CD pipelines (Azure DevOps, GitHub Actions).
• Strong analytical and troubleshooting skills.
• Prior experience working in Agile methodologies.
• Ability to prioritize multiple tasks independently and mentor team members.

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