AI Data Engineer

Role AI Data Engineer

Role Overview:

YOE: 5+

Work Mode: 4+1 Hybrid

Number of Openings: 1

Job Description: The AI Data Engineer will be responsible for designing, building, and operating scalable data pipelines and curated data assets that power machine learning, generative AI, and intelligent automation solutions in an SLA-driven managed services environment. This role focuses on data ingestion, transformation, governance, and operational reliability across cloud and hybrid environments enabling use cases such as knowledge retrieval (RAG), conversational AI, predictive analytics, and AI-assisted service management. The ideal candidate combines strong data engineering fundamentals with an understanding of AI workload requirements, including quality, lineage, privacy, and performance.

Key Responsibilities Design, build, and operate production-grade data pipelines that support AI/ML and generative AI workloads in managed services environments Develop curated, analytics-ready datasets and data products to enable model training, grounding, feature generation, and AI search/retrieval

Implement data ingestion patterns for structured and unstructured sources (APIs, databases, files, event streams, documents)

Build and maintain transformation workflows with strong testing and validation Enable Retrieval-Augmented Generation (RAG) by preparing document corpora, chunking strategies, metadata enrichment, and vector indexing pattern

s Integrate data pipelines with application services Support ITSM and enterprise workflow data needs, including ServiceNow data integration, CMDB/incident data quality improvements, and automation enablement

Implement observability for data pipelines (monitoring, alerting, SLAs/SLOs) and perform root cause analysis for pipeline failures or data quality incidents

Apply data governance and security best practices

Collaborate with ML Engineers, DevOps/SRE, and solution architects to operationalize end-to-end AI solutions

Contribute to reusable patterns, templates, and standards within the Bell Techlogix AI Center of Excellence Required Qualifications

Bachelors degree in Computer Science, Engineering, Information Systems, or equivalent practical experience

5+ years of experience in data engineering, analytics engineering, or platform data operations Strong proficiency in SQL and Python; experience with data modeling and dimensional concepts Hands-on experience with Azure data services (e.g., Data Factory, Synapse, Databricks, Storage, Key Vault) or equivalent cloud tooling

Experience building reliable pipelines with scheduling, dependency management, and automated testing/validation Experience supporting production data platforms with incident management, troubleshooting, and root cause analysis

Understanding of data security, privacy, and governance principles in enterprise environments Preferred Qualifications Experience enabling AI/ML workloads: feature engineering, training data preparation, and integration with Azure Machine Learning

Experience with unstructured data processing for generative AI Familiarity with vector databases or vector search and RAG patterns

Experience with event streaming and messaging

Familiarity with ServiceNow data model and integration patterns (Table API, export, CMDB/ITSM reporting)

Relevant certifications (Microsoft Azure Data Engineer, Azure AI Engineer, Databricks)