Data Engineer — Scalable ML Pipelines & Analytics

sportygroup; United States; Remote; USD 110,000 - 160,000; Full time

Job summary

sportygroup is seeking a Data Engineer to design and maintain data infrastructure powering ML and analytics for a fast-growing digital business. The role focuses on scalable pipelines, data quality, and architecture to handle high daily changes.

You will collaborate with data scientists, MLOps, product owners, and BI analysts to translate business processes into robust data systems and features.

Qualifications

• Bachelor's degree or equivalent in a technical field
• 3+ years of data engineering or related experience
• Hands-on with data pipelines, warehouses, and data integration
• Production experience with relational and NoSQL databases and data modelling

Responsibilities

• Design, develop, and maintain scalable batch ETL and near-real-time data pipelines across diverse, high-velocity sources
• Ensure data quality, accuracy, and consistency across the platform
• Identify and implement internal process improvements to optimize data delivery and re-architect infrastructure for scalability
• Build new API integrations to support growing data volume and complexity

Skills

SQL

Python

Apache Airflow

Apache Spark

AWS

Data modelling

Event-driven architectures

Education

Bachelor's degree or equivalent

Tools

Apache Airflow

Apache Spark

AWS Redshift

AWS S3

AWS Athena

EC2

Lambda

Job description

sportygroup is seeking a Data Engineer to design and maintain data infrastructure powering ML and analytics for a fast-growing digital business. The role focuses on scalable pipelines, data quality, and architecture to handle high daily changes.

You will collaborate with data scientists, MLOps, product owners, and BI analysts to translate business processes into robust data systems and features.