Manager, Data Engineering at Purchasing Power
Atlanta, Georgia, USA -
Full Time


Start Date

Immediate

Expiry Date

08 Nov, 25

Salary

0.0

Posted On

09 Aug, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Computer Science, Performance Tuning, Control Center, Cluster Management, Distributed Systems, Apache Kafka, Stream Processing, Communication Skills, Data Processing, Mathematics

Industry

Information Technology/IT

Description

WORK AT PURCHASING POWER

Position: Manager, Data Engineering
Location: Atlanta/Hybrid work model
Who Are We: Purchasing Power (corp.purchasingpower.com)
We are an Atlanta-based voluntary benefit company offering an industry-leading employee purchase program for brand-name consumer products, online education services and travel offerings through convenient payroll deduction, helping employees achieve financial flexibility.
The Opportunity: The Manager of Data Engineering will lead our data platform team in building and scaling enterprise-grade streaming data architectures. You will be a technical leader with deep expertise in the Confluent platform, Apache Kafka, and modern data engineering practices. This role will be responsible for managing a team of data engineers while driving the strategic direction of our real-time data infrastructure.

THE EXPERIENCE YOU WILL BRING:

  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or related technical field
  • 2+ years of people management experience leading technical teams
  • 5+ years of hands-on data engineering experience with distributed systems
  • Deep expertise in Confluent Platform including Kafka Connect, Schema Registry, ksqlDB, and Control Center
  • Proficiency in Kafka cluster sizing, scaling, and performance optimization
  • Advanced proficiency in Apache Kafka: stream processing, topic design, partitioning strategies, consumer groups, and performance tuning
  • Extensive experience with Apache Airflow for workflow orchestration, DAG development, and pipeline monitoring
  • Expert-level skills in PySpark for large-scale data processing, performance optimization, and cluster management
  • Strong communication skills for working with technical and business stakeholders
  • Proven experience designing event-driven architectures and real-time data pipelines

How To Apply:

Incase you would like to apply to this job directly from the source, please click here

Responsibilities

Loading...