Data Engineer IV

About the role

We're looking for a data engineer with a strong technical background in data engineering and AI enablement, plus functional expertise in customer experience insights, particularly in customer support and operations. To excel in this role, you'll need to be passionate about data, adept at managing multiple projects simultaneously, and thrive in a fast-paced environment. You should also have excellent organizational and presentation skills, build and maintain strong relationships with internal partners and stakeholders, and demonstrate a proven ability to work effectively in cross-functional teams.

At OP, we help you harness the power of technology for maximum impact. A technology consulting and solutions company, we offer advisory and managed services, innovative platforms, and staffing solutions across a wide range of fields including AI, cyber security, enterprise architecture, and beyond. For nearly two decades, we've been challenging the status quo of the consulting industry serving up fresh, ingenious thinking through a radically lean structure. Together, this strategy delivers unprecedented performance at an unparalleled pace for faster results that propel your business forward.

Responsibilities

• Data Engineering & Architecture (40%): Design, develop, integrate, launch, and maintain scalable data pipelines (batch and streaming) that support multiple use cases across PSO. Build and optimize ETL/ELT workflows, data models, and data warehouse architectures to facilitate efficient development of data artifacts. Implement data quality frameworks including validation, monitoring, alerting, and lineage tracking to ensure data reliability. Develop and manage orchestration workflows (e.g., Airflow, Dataswarm) for scheduling and dependency management of data pipelines. Optimize query performance, pipeline efficiency, and storage costs across large-scale data infrastructure.
• Analytics & Visualization (20%): Create interactive and dynamic data visualizations that communicate complex insights to stakeholders. Work with various data sources, including customer interactions, feedback, behavioral data, and operational logs, to integrate and build reports that identify pain points and trends. Develop and track key performance indicators to measure the effectiveness of customer experience initiatives.
• AI Enablement & Automation (40%): Enable AI/ML-powered analytics by building and maintaining feature pipelines, curated datasets, and model-ready data assets. Leverage large language models (LLMs) and generative AI tools to automate data workflows, accelerate insight generation, and enhance self-service capabilities for stakeholders. Develop and maintain prompt engineering frameworks, AI-assisted reporting tools, and intelligent automation solutions that scale team productivity. Partner with engineering and data science teams to integrate AI/ML model outputs into dash