Real-Time Data Engineer: Event-Driven & AI Workflows

Socket.dev; Tampa (FL); On-site; USD 100,000 - 160,000; Full time

Benefits offered by this job

Medical coverage

Unlimited PTO

401(k) matching

Job summary

Apex Service Partners is seeking a Data Engineer to own the core data infrastructure, from capture at the source to downstream actions. You will build real-time pipelines, automate event-driven workflows, and partner with analytics to support AI-driven systems.

The role emphasizes delivering reliable data platforms, streaming architectures, and scalable ingestion across APIs and internal systems, with a focus on accuracy and automation in a fast-paced environment.

Qualifications

• Bachelor's or Master's degree in Computer Science/Data Engineering or related field.
• 5+ years of data engineering experience designing/operating event-based architectures.
• Experience with streaming pipelines (Kafka, Event Hubs, Kinesis, Spark Streaming).
• Strong Python proficiency for data ingestion frameworks and pipelines.

Responsibilities

• Design, build, and maintain event-driven data architectures for real-time data flows.
• Develop and manage streaming pipelines for low-latency analytics.
• Build robust Python data ingestion pipelines from APIs, databases, and streams.
• Integrate data across multiple APIs and internal systems with well-documented flows.
• Design event-driven automated workflows with logging and error handling.
• Advance data platform roadmaps and support BI/semantic models.
• Ensure data quality and pipeline reliability end-to-end.

Skills

Python

Azure

Data streaming

APIs

SQL

Airflow

Spark

Education

Bachelor's degree

Master's degree

Tools

Azure Event Hubs

Kafka

Airflow

Databricks

Job description

Apex Service Partners is seeking a Data Engineer to own the core data infrastructure, from capture at the source to downstream actions. You will build real-time pipelines, automate event-driven workflows, and partner with analytics to support AI-driven systems.

The role emphasizes delivering reliable data platforms, streaming architectures, and scalable ingestion across APIs and internal systems, with a focus on accuracy and automation in a fast-paced environment.