Note: The job is a remote job and is open to candidates in USA. itD is seeking a Data Engineer IV – Customer Experience & AI Enablement to build scalable data infrastructure, self-service analytics capabilities, and AI-enabled data solutions that support global customer experience and post-sales operations. The ideal candidate will bring deep experience in data engineering, large-scale ETL/ELT pipeline development, workflow orchestration, and analytics enablement.
Responsibilities
- Design, develop, integrate, and maintain scalable batch and streaming data pipelines that support customer experience, customer support, survey, and digital support analytics use cases
- Build and optimize production-grade ETL/ELT workflows, data models, and data warehouse architectures to enable efficient, reliable, and scalable analytics
- Develop and maintain workflow orchestration processes for pipeline scheduling, dependency management, monitoring, and operational reliability
- Create interactive self-service dashboards and data visualizations that provide stakeholders with visibility into customer experience trends, operational metrics, and key performance indicators
- Implement data quality, validation, monitoring, alerting, governance, and lineage practices to ensure the accuracy, reliability, and usability of enterprise data assets
- Enable AI and machine learning analytics by developing curated datasets, feature pipelines, model-ready data assets, and AI-assisted analytical workflows
- Leverage large language models and generative AI capabilities to automate data workflows, accelerate insight generation, and reduce manual operational effort
- Partner with analysts, data scientists, engineering teams, customer support, and operations stakeholders to translate data requirements into scalable technical solutions
- Optimize complex SQL queries, data pipelines, storage utilization, and large-scale data processing workflows to improve performance and efficiency
- Champion data literacy and AI enablement through technical documentation, training, best-practice development, and knowledge sharing across cross-functional teams
- Attend regular internal practice community meetings
- Collaborate with your itD practice team on industry thought leadership
- Complete client case studies and learning material, including blogs and media material
- Build out material to contribute to the Digital Transformation practice
- Attend internal itD networking events, both in person and virtual
- Work with leadership on career fast-track opportunities
Skills
- 6+ years of experience in data engineering, quantitative analytics, operational analytics, or related technical data roles
- Strong proficiency in SQL, including complex queries, query optimization, performance tuning, and window functions
- Strong Python programming experience for data engineering, automation, and large-scale data processing
- Demonstrated experience designing and building production-grade ETL/ELT pipelines and scalable data integration workflows
- Experience with workflow orchestration tools such as Apache Airflow or equivalent data pipeline orchestration technologies
- Experience with large-scale data processing and data warehousing technologies such as Apache Spark, Hive, Presto, Snowflake, or BigQuery
- Hands-on experience building self-service dashboards and data visualizations using Tableau, Looker, or equivalent business intelligence platforms
- Experience developing data models and applying dimensional modeling concepts, including star and snowflake schemas
- Demonstrated experience implementing data quality frameworks, validation processes, monitoring, alerting, and data governance standards
- Experience manipulating large datasets to generate actionable insights and deliver scalable data solutions
- Ability to independently manage multiple technical projects, navigate ambiguity, and deliver data solutions in a fast-paced environment
- Experience communicating complex technical and data concepts to both technical and non-technical stakeholders
- Bachelor's degree in Computer Science or a related technical field
- Hands-on experience with Generative AI technologies, large language models, or AI-enabled analytics and automation solutions
- Experience with prompt engineering, retrieval-augmented generation architectures, LLM APIs, or AI agent workflows
- Experience building feature pipelines, curated datasets, or model-ready data assets supporting machine learning and AI use cases
- Experience integrating AI or machine learning outputs into dashboards, reporting tools, or operational workflows
- Experience with streaming data technologies such as Kafka or Spark Streaming
- Familiarity with Git, CI/CD practices for data pipelines, and infrastructure-as-code methodologies
- Knowledge of metadata management, data cataloging, and data lineage technologies
- Experience with customer experience, customer support, contact center, or post-sales operations data and metrics
- Experience working with customer support or CRM platforms such as Salesforce
- Experience with digital analytics platforms such as Google Analytics or Adobe Analytics
- Experience using Python or Bash scripting to automate workflows and build internal data tooling
- Familiarity with Agile development methodologies
- Experience working in fast-paced technology, startup, consumer electronics, or high-volume consumer product environments
- Prior contingent workforce or contractor experience supporting large-scale technology organizations
Benefits
- Comprehensive medical benefits
- A 401k plan
- Paid holidays
- Medical, dental, vision, life insurance
- Paid holidays
- 401K + matching
- Networking & career learning and development programs
Company Overview