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Data Engineer

4 months ago

Cincinnati, United States Qual IT Resources Full time

Data Engineer- Level 2- Job Description

As a Data Engineer, you will have the opportunity to build solutions that ingest, transform, store, and distribute our data products to be consumed by data scientists and our products.


Required Experience:

  • 4+ years of PySpark
  • 4+ years of Python
  • 4+ years of Data Development, Data Warehousing, and ETL concepts


  • 2+ years of Azure with focus in the following areas:

*Security Concepts

*Domain Concepts

*Storage Accounts

*Key Vaults and Secrets


  • Databricks Skills 2+ years of Databricks with focus in the following areas:

*Notebooks

*Delta Live Tables

*Databricks Asset Bundles

*Cluster Configuration and Management

*Unity Catalog



  • 3+ years of SDLC with focus in the following areas:

*CI/CD Concepts

*Git, GitHub Repositories

*Automated Testing (Unit Testing, Integration Testing, Regression Testing)



Key Responsibilities

-Design, develop, and implement integrations based on use feedback.


-Troubleshoot production issues and coordinate with the development team to streamline code deployment.


-Implement automation tools and frameworks (CI/CD pipelines).


-Analyze code and communicate detailed reviews to development teams to ensure a marked improvement in applications and the timely completion of products.


-Collaborate with team members to improve the company’s engineering tools, systems and procedures, and data security.


-Deliver quality customer service and resolve end-user issues in a timely manner


-Draft architectural diagrams, interface specifications and other design documents


-Participate in the development and communication of data strategy and roadmaps across the technology organization to support project portfolio and business strategy


-Innovate, develop, and drive the development and communication of data strategy and roadmaps across the technology organization to support project portfolio


-Drive the development and communication of enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses


-Drive digital innovation by leveraging innovative new technologies and approaches to renovate, extend, and transform the existing core data assets, including SQL-based, NoSQL-based, and Cloud-based data platforms


-Define high-level migration plans to address the gaps between the current and future state, typically in sync with the budgeting or other capital planning processes


-Lead the analysis of the technology environment to detect critical deficiencies and recommend solutions for improvement


-Mentor team members in data principles, patterns, processes and practices


-Promote the reuse of data assets, including the management of the data catalog for reference


-Draft and review architectural diagrams, interface specifications and other design documents