Data Engineer (Databricks Experience)

Infinitive IncMcLean, IL
Onsite

About The Position

We are seeking a highly skilled Senior Data Engineer to join our dynamic team. The ideal candidate will have a strong background in data engineering, with expertise in Databricks, DevOps tools (Jenkins/Terraform), and data modeling concepts (3NF, Dimensional, Data Vault). As a Senior Data Engineer, you will play a critical role in designing, implementing, and maintaining our client's data infrastructure while ensuring scalability, reliability, and efficiency.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, or related field.
  • Proven experience as a Data Engineer, preferably in a cloud-based environment.
  • Strong proficiency in Databricks for data processing and analytics.
  • Hands-on experience with DevOps tools such as Jenkins and Terraform for infrastructure automation.
  • In-depth knowledge of data modeling concepts including 3NF, Dimensional, and Data Vault.
  • Proficiency in SQL and programming languages such as Python or Scala.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Excellent problem-solving skills and attention to detail.
  • Strong communication and collaboration skills.
  • Applicants for employment in the U.S. must possess work authorization which does not require sponsorship by the employer for a visa.

Nice To Haves

  • Master’s degree preferred.

Responsibilities

  • Design, build, and maintain scalable data pipelines and ETL processes using Databricks and other relevant technologies.
  • Implement continuous integration and continuous deployment (CI/CD) pipelines using Jenkins and Terraform to automate deployment, monitoring, and scaling of data infrastructure.
  • Develop and implement data models based on business requirements, including 3NF, Dimensional, and Data Vault models. Ensure data models adhere to best practices for efficiency, scalability, and maintainability.
  • Identify and address performance bottlenecks in data pipelines and queries. Optimize data processing and storage to improve overall system performance.
  • Implement data quality checks and monitoring processes to ensure data accuracy, completeness, and consistency.
  • Work closely with cross-functional teams including data scientists, analysts, and software engineers to understand data requirements and deliver high-quality solutions.
  • Document data pipelines, infrastructure configurations, and data models. Define and enforce best practices for data engineering and DevOps processes.
  • Provide guidance and mentorship to junior team members. Conduct training sessions to promote knowledge sharing and skill development within the team.
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