Data Engineer, Microsoft Fabric and AI Director

GS1•Ewing Township, NJ

2d•$140,000 - $160,000

About The Position

GS1 Global Office is seeking a Data Engineer Director to join the Business Intelligence and Data Analytics team. The role will design, build and support secure, scalable enterprise data and analytics solutions using Microsoft Fabric, Azure data services and Power BI. It will also develop AI-enabled data pipelines that connect approved enterprise data with large language model platforms, including Claude AI and other approved enterprise AI tooling. This is a senior, hands-on individual-contributor role combining data engineering, business intelligence, AI-enabled solution development and production support. The role will provide technical leadership, establish reusable engineering standards and work with stakeholders across GS1 Global Office and Member Organisations to translate business needs into reliable, well-governed data products.

Requirements

Bachelor’s degree in computer science, data engineering, information systems or a related field, or equivalent relevant professional experience.
At least five years of relevant experience in data engineering, business intelligence or analytics, including responsibility for production solutions.
Strong practical experience with Microsoft Fabric, or significant experience with Azure Synapse, Databricks or comparable modern cloud analytics platforms.
Strong experience developing Power BI reports, semantic models and datasets.
Advanced SQL skills and experience with Azure SQL or comparable relational database services.
Practical experience building ETL or ELT solutions using Azure Data Factory, Microsoft Fabric Data Pipelines or comparable orchestration tools.
Experience with dimensional modelling, data warehousing and enterprise semantic models, including DAX.
Proficiency with Python and/or PySpark for data processing and automation.
Practical experience building or supporting RAG pipelines and working with large language model APIs, such as Claude, OpenAI or comparable platforms.
Experience with embeddings, vector search or vector databases, prompt-based retrieval patterns and structured and unstructured data integration.
Experience with source control, automated testing, CI/CD and production monitoring.
Experience implementing data security, role-based access controls and privacy requirements in cloud data and analytics environments.
Strong analytical and problem-solving skills, with the ability to diagnose complex technical and data-quality issues.
Ability to work independently while collaborating effectively across technical teams, functions, locations and cultures.
Strong communication and stakeholder-engagement skills, including the ability to explain technical topics clearly to non-technical audiences.
Sound judgement when working with sensitive, confidential or restricted information.
Ability to manage competing priorities and switch effectively between engineering, reporting and operational-support activities.
Pragmatic, hands-on and focused on reliable outcomes and measurable value.
Commitment to documentation, knowledge sharing, continuous improvement and ongoing learning.
Fluent written and spoken English.

Nice To Haves

Microsoft Fabric or related Microsoft data-platform certification.
Experience with Microsoft Purview, OneLake, Azure DevOps or GitHub.
Experience with Power BI administration, tenant governance or capacity management.
Experience with large-scale analytical datasets and cloud cost optimisation.
Experience with Claude AI, Claude Code or comparable enterprise AI coding and knowledge-work tools.
Knowledge of AI governance, responsible AI, model evaluation and enterprise data-privacy practices.
Experience working in a global, federated or matrixed organisation.

Responsibilities

Design, develop and maintain scalable data pipelines using Microsoft Fabric and Azure data services.
Build and support Lakehouse, Data Warehouse and semantic model solutions using appropriate architecture and reusable design patterns.
Develop reliable data integration processes using Microsoft Fabric Data Pipelines, Azure Data Factory, APIs and other approved integration methods.
Support migration and modernisation initiatives involving Microsoft Fabric and Azure analytics services.
Optimise data processing performance, scalability, maintainability and cost efficiency.
Contribute to enterprise data architecture decisions and the evolution of shared data models and analytics standards.
Design and build retrieval-augmented generation pipelines that securely connect approved enterprise data to Claude AI and other approved large language model platforms.
Develop data preparation, chunking, embedding, indexing and retrieval processes that support accurate and traceable AI-enabled search and analytics.
Support the responsible adoption of approved enterprise AI and development tools, including Claude AI and Claude Code, with secure data-handling and access patterns.
Evaluate and prototype AI-enabled analytics use cases with senior leaders and technical stakeholders, considering business value, architecture, risk and guardrails.
Monitor and improve AI pipeline reliability, quality, performance and cost in line with GS1 governance standards.
Maintain appropriate documentation, traceability and human oversight for AI-enabled solutions.
Develop and maintain Power BI dashboards, reports, datasets and semantic models that provide clear and actionable insights.
Support operational reporting, data-quality reporting and prioritised ad hoc analytics requests.
Work with business stakeholders to understand requirements, define acceptance criteria and translate needs into sustainable reporting solutions.
Promote consistent definitions, measures and reporting practices across the organisation.
Implement data validation, observability, monitoring and quality controls across data pipelines and analytics solutions.
Support metadata management, data lineage, documentation, retention and governance requirements.
Design solutions in accordance with GS1 information security, data privacy, access-control and responsible AI requirements.
Implement role-based access controls, data classification and auditability appropriate to the sensitivity and intended use of the data.
Identify and escalate data-quality, security, privacy, model-risk and governance concerns.
Develop automated testing and validation for data pipelines, semantic models, reports and AI-enabled solutions.
Use Git, source control, CI/CD and environment-management practices to support reliable deployment across development, test and production environments.
Monitor critical solutions, resolve production incidents and troubleshoot pipeline failures, refresh errors, reporting issues, RAG pipeline errors and performance bottlenecks.
Conduct root-cause analysis and implement preventative improvements.
Maintain technical documentation, operational runbooks and recovery procedures, and contribute to release validation and business-continuity activities.
Provide technical leadership on data architecture, solution design, engineering standards and responsible AI implementation.
Review code and solution designs, share knowledge and coach other team members in data engineering and analytics practices.
Partner with Product Owners, Data Engineers, QA, Software Engineering and business stakeholders across a globally distributed organisation.
Communicate technical options, dependencies, risks and costs clearly to technical and non-technical audiences.
Assess trade-offs and make recommendations that balance business value, usability, security, scalability, cost and maintainability.
Contribute to planning, architecture discussions, continuous improvement and workload priorities across the BIDA team.