Remote Data Engineer — Scalable Pipelines & Kafka

iGaming Centre; New York (NY); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Global Employee Assistance Programme

Calm and Reulay app

Online training videos

Flexible working hours

Teambuilding events

Job summary

iGaming Centre is seeking a Data Engineer to build and optimize large-scale data pipelines for sport performance analytics. You will design Nifi-based ingestions within AWS, implement ETL using Python/Java, and ensure robust data models and observability across the system.

The role emphasizes real-time and batch data processing, unit testing, and cross-team collaboration to enhance scalability and data quality. Remote work from anywhere in the U.S. is possible.

Qualifications

• Master’s degree in Computer Science, Computer Engineering, or closely related field and 1 year experience as a data engineer or related occupation.
• Proficiency in Python/Java, ETL development, SQL analytics, and Agile practices.
• Experience designing data architecture and data models.

Responsibilities

• Design, build, and implement large-scale data pipelines using Nifi for analytics and data science in Sport Performance products.
• Develop scalable Nifi ingestion pipelines in AWS to process real-time and batch data.
• Implement ETL/warehousing using Python and Java; add triggers, filters, monitoring, and observability.
• Establish unit tests and data models for ETL systems; ensure data quality and logging.
• Utilize Kafka to store and move data across pipelines for downstream analytics.
• Collaborate with engineering teams to improve scalability and consistency across systems.
• Adhere to company standards; use JIRA for agile data development and project alignment.

Skills

Python

Java

Kafka

AWS

Docker

ETL Development

Warehousing

SQL

Agile

Data architecture

Education

Master’s degree in Computer Science/Computer Engineering or related field

Tools

Nifi

Job description

iGaming Centre is seeking a Data Engineer to build and optimize large-scale data pipelines for sport performance analytics. You will design Nifi-based ingestions within AWS, implement ETL using Python/Java, and ensure robust data models and observability across the system.

The role emphasizes real-time and batch data processing, unit testing, and cross-team collaboration to enhance scalability and data quality. Remote work from anywhere in the U.S. is possible.