Cloud Data Engineer – ETL Pipelines & Real-Time Data

Cincinnati Reds; Cincinnati (OH); On-site; USD 110,000 - 140,000; Full time

Job summary

The Cincinnati Reds are seeking a Data Engineer to join the Information Technology – Baseball Data & Development team. You will design, build, and maintain data pipelines, collecting and transforming data from multiple sources for use by analysts and systems.

The ideal candidate excels at automating data workflows, has cloud experience (Azure, AWS, GCP), strong Python (PySpark), SQL optimization, and familiarity with ETL/ELT, IaC, and modern workflow tools like Airflow, Dagster, or Prefect.

Qualifications

• Bachelor's degree or equivalent in a computational science or technical field.
• 2+ years of professional data engineering experience.
• Strong SQL skills with query optimization and indexing.
• Python experience for data processing (PySpark).
• Experience with cloud platforms (Azure, AWS, GCP) and ETL/ELT.

Responsibilities

• Pipeline Development – Build, optimize, and maintain ETL/ELT pipelines.
• Data Optimization – Write efficient SQL queries and tuning.
• Cloud & Workflow Management – Use cloud tools and Airflow-based schedulers.
• System Management – Monitor and troubleshoot data systems.
• Collaboration & Process – Participate in code reviews and improve workflows.
• Other – Take on additional duties as needed.

Skills

SQL Proficiency

Query optimization

Indexing strategies

Python (PySpark)

DevOps practices

Git & CI/CD (Azure DevOps)

Cloud platforms (Azure, AWS, GCP)

ETL/ELT pipelines

IaC (Terraform, CloudFormation)

Real-time processing (Kafka, Kinesis)

Workflow orchestration (Airflow, Dagst

Education

Bachelor's degree in computational science or technical field

Tools

Azure DevOps

Terraform

CloudFormation

Kafka

Kinesis

Airflow

Dagster

Prefect

Job description

The Cincinnati Reds are seeking a Data Engineer to join the Information Technology – Baseball Data & Development team. You will design, build, and maintain data pipelines, collecting and transforming data from multiple sources for use by analysts and systems.

The ideal candidate excels at automating data workflows, has cloud experience (Azure, AWS, GCP), strong Python (PySpark), SQL optimization, and familiarity with ETL/ELT, IaC, and modern workflow tools like Airflow, Dagster, or Prefect.