Note: The job is a remote job and is open to candidates in USA. Confidential is seeking a Data Engineer to join a global Customer Experience team focused on using data, analytics, and AI to drive business improvements. The role involves building scalable data pipelines and architectures, developing analytics and self-service dashboards, enabling AI-driven automation, and partnering with cross-functional teams to improve customer experience operations.
Responsibilities
- Design, develop, integrate, launch, and maintain scalable batch and streaming data pipelines
- Build and optimize ETL/ELT workflows, data models, and data warehouse architectures
- Implement data quality frameworks, including validation, monitoring, alerting, and lineage tracking
- Develop and manage workflow orchestration processes for scheduling and dependency management
- 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 customer interactions, feedback, behavioral data, and operational data to identify pain points and trends
- Develop and track key performance indicators to measure the effectiveness of customer experience initiatives
- Build self-service dashboards and reports that provide actionable business insights
- 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 and accelerate insight generation
- Develop and maintain prompt engineering frameworks, AI-assisted reporting tools, and intelligent automation solutions
- 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 improve analytics and data engineering capabilities
- Work closely with customer service, operations, product, and engineering teams to integrate data insights into business decisions
- Support customer experience improvements through data-driven insights
- Promote data literacy and AI enablement through documentation, training, and best-practice sharing
Skills
- 8+ years of experience performing quantitative and operational analysis within customer support/service, e-commerce, order management, or comparable environments
- Strong data engineering experience designing and building production-grade data pipelines, data models, and ETL/ELT processes at scale
- Strong proficiency in SQL, including complex queries, performance tuning, and window functions
- Proficiency in at least one programming language, with Python preferred
- Experience with data warehousing platforms such as Hive, Presto, Spark, Snowflake, or BigQuery
- Experience with workflow orchestration tools such as Airflow or equivalent platforms
- Experience with data visualization tools such as Tableau, Looker, or equivalent
- Experience with data quality frameworks, data governance, and data modeling best practices
- Hands-on experience with AI/ML enablement, including feature pipelines, LLM-based tools, or AI-assisted analytics workflows
- Experience manipulating large datasets to formulate insights and drive solutions
- Proven ability to work independently, manage ambiguity, and deliver results
- Strong communication skills with the ability to articulate issues to both technical and non-technical audiences
- Cross-functional experience, including leading or influencing change through data-driven insights
- Strong experience designing and building production-grade data pipelines, data models, and ETL/ELT processes at scale
- Advanced SQL skills and proficiency in Python or another programming language
- Experience with data warehousing, workflow orchestration, and large-scale data infrastructure
- Experience implementing data quality frameworks, data governance, and data modeling best practices
- Hands-on experience with AI/ML workflows, LLM-based tools, or AI-assisted analytics
- Experience working with large datasets and creating self-service dashboards and visualizations
- Ability to work effectively with technical and non-technical stakeholders and translate data insights into business decisions
- Ability to manage ambiguity, prioritize multiple projects, and deliver results in a fast-paced environment
- Experience with generative AI tools and frameworks, including prompt engineering, RAG architectures, LLM APIs, or AI agent workflows
- Familiarity with Git, CI/CD for data pipelines, and infrastructure-as-code practices
- Experience with streaming data technologies such as Kafka or Spark Streaming
- Knowledge of metadata management, data cataloging, and data lineage tools
- Background in Customer Experience/Customer Support operations and related metrics
- Familiarity with customer support platforms such as Salesforce
- Experience with digital analytics tools such as Google Analytics or Adobe Analytics
- Experience with scripting for automation using Python, Bash, or similar technologies
- Experience building internal tooling
- Familiarity with Agile development methodologies
- Experience working in high-volume consumer products or electronics environments
- Experience supporting customer experience or customer support operations
- Generative AI experience, including prompt engineering, RAG, LLM APIs, or AI agent workflows
- Experience with streaming technologies such as Kafka or Spark Streaming
- Familiarity with Git, CI/CD, and infrastructure-as-code
- Knowledge of metadata management, data cataloging, and data lineage
- Customer Experience or Customer Support operations experience
- Experience with Salesforce or similar customer support platforms
- Experience with Google Analytics, Adobe Analytics, or similar digital analytics tools
- Experience with Python/Bash automation and internal tooling
- Familiarity with Agile methodologies
- Experience in high-volume consumer products or electronics environments
Benefits
- For eligible employees in the United States: comprehensive healthcare coverage, including medical, dental, and vision plans.
- For eligible employees in the United States: supplemental coverage, including accident insurance, critical illness insurance, and hospital indemnity.
- For eligible employees in the United States: 401(k) retirement savings.
- For eligible employees in the United States: life and disability insurance.
- For eligible employees in the United States: an employee assistance program.
- For eligible employees in the United States: legal support.
- For eligible employees in the United States: pet insurance.
- For eligible employees in the United States: employee discounts with preferred vendors.
Company Overview
Company H1B Sponsorship