Data Engineer – Self Service Analytics and Real Time Data Platforms

Role Overview

The Data Engineering team is seeking a Data Engineer to build scalable data products, semantic layers, and real-time data platforms. The role involves designing, developing, and maintaining batch and near real-time streaming data pipelines, as well as enabling self-service analytics through governed and reusable business data models.

What You Will Do

Design and develop scalable batch and near real-time streaming data pipelines, implement monitoring and operational best practices, and develop governed data access patterns for AI and conversational analytics applications.

Why It Might Be a Fit

The ideal candidate will have 2-4+ years of experience in data engineering, data pipeline development, and related fields, with a solid foundation in modern data engineering principles, distributed systems design, and cloud-native architectures.

Requirements

• Advanced Data Pipeline & ETL/ELT Expertise
• 2–4+ years of experience building and scaling ETL/ELT pipelines in production environments
• Proven experience with workflow orchestration tools such as Airflow, Composer, or similar platforms
• Working knowledge of distributed data processing concepts
• Expert-level SQL skills for large-scale transformation and analytics
• Experience designing scalable warehouse schemas and ML-ready data layers
• Proficiency in Python (or similar language) for data processing and ML pipeline integration
• Experience integrating data pipelines with ML platforms such as Vertex AI (preferred), Databricks ML, or equivalent
• Experience building real-time data pipelines using Kafka, Pub/Sub, or similar technologies
• Knowledge of feature streaming, low-latency data processing, and event-driven architectures
• Ability to work closely with the streaming team to architect and build real-time dashboards using Superset
• Experience designing cloud-native data architectures (GCP preferred)
• Experience with lakehouse architectures and cloud data warehouses
• Knowledge of vector databases, embeddings pipelines, and AI-serving infrastructure is a plus

Benefits

• Medical, dental, vision
• 401(k) plan
• Life insurance coverage
• Disability benefits
• Tuition assistance program
• PTO

Tagged as: Pipeline Management, Python, SQL