CX Data Engineer

Insight Global; Sunnyvale (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Insight Global is seeking a Data Engineer IV to join a global team driving AI-enabled analytics and scalable data architectures. You will design and optimize data pipelines, implement data quality, and develop AI-powered workflows to accelerate insights for customer care and operations.

You will partner with engineering and data science to integrate AI outputs into dashboards and workflows, while building governance and data visualization best practices across teams.

Qualifications

• 6+ years of experience doing quantitative and operational analyses in a customer support/service, post sales, e-commerce, or order management organization.
• Strong data engineering skills: production-grade data pipelines, data models, and ETL/ELT processes at scale.
• Proficiency in SQL (complex queries, performance tuning, window functions) and at least one programming language (Python preferred).
• Experience with data visualization tools such as Tableau, Looker, or equivalent for creating self-service dashboards.
• Experience with data warehousing platforms (e.g., Hive, Presto, Spark, Snowflake, or BigQuery).
• Experience with workflow orchestration tools (e.g., Airflow, Dataswarm, or equivalent) - Experience with generative AI tools and frameworks (e.g., prompt engineering, RAG architectures, LLM APIs, or AI agent workflows).
• Previous Meta experience

Responsibilities

• 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.
• 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.
• 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 dashboards and operational workflows.
• Evaluate and implement emerging AI tools and techniques to continuously improve the team's analytics and data engineering capabilities.
• Cross-Functional Partnership
• Work closely with customer service and operations, product, and engineering teams to integrate data insights into business decisions and drive customer experience improvements.
• Champion data literacy and AI enablement across the organization through documentation, training, and best practice sharing.

Skills

SQL proficiency

Python programming

Data visualization

Data warehousing

Workflow orchestration

Generative AI tools

Meta experience

Tools

Airflow

Dataswarm

Tableau/Looker

Hive

Presto

Spark

Snowflake

BigQuery

Job description

Job Description

As a Data Engineer, you will be part of a global team that unlocks the power of customer feedback and insights to drive business improvements. Your background and experience in building scalable data pipelines, designing robust data architectures, and creating insightful self-service dashboards will provide visibility into the health of our key business metrics, enabling us to deliver insights that enhance customer experiences. You will also play a key role in enabling AI-driven analytics and automation capabilities across the team—leveraging large language models, machine learning workflows, and intelligent tooling to accelerate insight generation and operational efficiency. Additionally, you will contribute to the development of data governance policies, data quality standards, and data visualization best practices, ensuring the accuracy, reliability, and actionability of our data assets.

We're seeking a data engineer with a strong technical background in data engineering and AI enablement, combined with functional expertise in customer experience insights—specifically 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 possess excellent organizational and presentation skills, be able to build and maintain strong relationships with internal partners and stakeholders, and demonstrate a proven ability to work effectively within cross‑functional teams.

Data Engineer IV 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 dashboards and operational workflows

Evaluate and implement emerging AI tools and techniques to continuously improve the team's analytics and data engineering capabilities

Cross-Functional Partnership

Work closely with customer service and operations, product, and engineering teams to integrate data insights into business decisions and drive customer experience improvements

Champion data literacy and AI enablement across the organization through documentation, training, and best practice sharing

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [e-mail] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

• 6+ years of experience doing quantitative and operational analyses in a customer support/service, post sales, e-commerce, or order management organization

• Strong data engineering skills: experience designing and building production‑grade data pipelines, data models, and ETL/ELT processes at scale

• Proficiency in SQL (complex queries, performance tuning, window functions) and at least one programming language (Python preferred)

• Experience with data visualization tools such as Tableau, Looker, or equivalent for creating self‑service dashboards

• Experience with data warehousing platforms (e.g., Hive, Presto, Spark, Snowflake, or BigQuery)

• Experience with workflow orchestration tools (e.g., Airflow, Dataswarm, or equivalent) - Experience with generative AI tools and frameworks (e.g., prompt engineering, RAG architectures, LLM APIs, or AI agent workflows)

• Previous Meta experience