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Data Integration Engineer - Technical Lead

Job in Atlanta, Fulton County, Georgia, 30383, USA
Listing for: TechDigital Group
Full Time position
Listed on 2025-12-27
Job specializations:
  • Software Development
    Data Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Position: Staff Data Integration Engineer - Technical Lead

Required skillset:

  • Maven, XML, Web Services, Spring MVC
  • Kafka
  • Job Summary:
    This position requires a team player who can wear multiple hats when needed. As a technical expert, you must be comfortable working across engineering domains on a variety of high impact projects. You will be a valued part of a group that is constantly maturing Kafka use and event-driven architecture. Members of this team are responsible for the overall use and implementation of Kafka components including the Confluent platform, observability, governance, best practices, and solution development.

    An advanced understanding of Kafka principles and enterprise integration patterns is required.

    In order to be successful:
    You are a team player. You are a self-directed person who can identify priorities. You are responsive and available for fast-paced operational and developer requests. You are a detail-oriented person who takes pride in keeping data correct and always having a backup plan. You are a problem-solver who might write some code or find a tool to get things done when there isn't an established solution.

    You are a leader in the event-driven world. You are a Kafka expert.

    Responsibilities:

  • Develop and implement solutions using Kafka in .NET, Node.js, and scripting.
  • Responsible for regular duties related to an on-call rotation.
  • Regular pair programming sessions with engineers.
  • Administer and improve use of Kafka across the organization including Kafka Connect, ksql

    DB, Streams, and custom implementations.
  • Work with multiple teams to ensure best use of Kafka and data-safe event streaming.
  • Develop deployment pipelines to Kubernetes for Kafka components.
  • Identify and monitor both self-managed and fully managed Kafka components.
  • Understand and apply event-driven architecture patterns and Kafka best practices.
  • #J-18808-Ljbffr
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