Data Engineer (AI Engineering)

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Data EngineerData
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Quick Summary

Key Responsibilities

Design, build, and maintain scalable, reliable data pipelines and lakehouse solutions on Microsoft Fabric, Synapse Analytics, and Azure. • AI engineering: Develop, integrate,

Requirements Summary

Working knowledge of D365 F&O (FinOps) — data entities, finance, sales, and supply chain modules, and how ERP data is extracted and modeled for analytics and reporting.

Technical Tools
Data EngineerData

The Data Engineer is responsible for building and scaling the data and AI foundations that power the business

across North America. Based in the NAM region and reporting to the Global Data Engineering Manager, this role designs and operates modern data pipelines and AI-enabled solutions on Microsoft Azure and Microsoft Fabric, transforming data from ERP, commerce, marketing, and customer platforms into reliable, production-grade products.

 

This is a hands-on, delivery-focused role at the intersection of data engineering and applied AI. The role partners closely with commercial, marketing, and technology stakeholders across the NAM region to accelerate growth, improve the customer experience and unlock new capabilities through data and AI.

 

Responsibilities

~1 min read

 

• Data pipelines & platform: Design, build, and maintain scalable, reliable data pipelines and lakehouse solutions on Microsoft Fabric, Synapse Analytics, and Azure. • AI engineering: Develop, integrate, and operationalize AI/ML and generative-AI solutions — from feature pipelines and model deployment to RAG, embeddings, and LLM-based applications — with a focus on production reliability. • Data modeling & quality: Build well-structured, governed data models; implement data quality, validation, lineage, and observability across the platform. • Integration: Ingest and unify data from ERP (Dynamics 365 Finance & Operations), commerce, marketing automation, and CRM systems to create a trusted view of customers, products, and orders across the NAM region. • Automation & MLOps: Apply CI/CD, infrastructure-as-code, orchestration, and MLOps practices to automate deployment, monitoring, and retraining. • Partnership: Work with business and technical stakeholders across the NAM region, and with global data and technology teams, to translate commercial needs into data and AI solutions that drive measurable outcomes. • Performance & cost: Optimize pipelines and workloads for performance, scalability, security, and cost efficiency in the cloud. • Governance & security: Ensure solutions meet data governance, privacy, and security standards across the NAM markets in which we operate.

 

Requirements

~1 min read

 

Experience / Training / Education · 3–5 years in data engineering, with demonstrated delivery of production data and/or AI solutions. · ERP (Dynamics 365 Finance & Operations): Working knowledge of D365 F&O (FinOps) — data entities, finance, sales, and supply chain modules, and how ERP data is extracted and modeled for analytics and reporting. · Microsoft Fabric: Hands-on experience delivering with Fabric — Lakehouse and Warehouse, Data Factory pipelines, Spark notebooks, semantic models, Mirroring, and Shortcuts. Awareness of capacity (CU / F-SKU) consumption and cost management is highly valued. · AI engineering: Practical experience designing, building, and deploying AI/ML solutions using Microsoft Foundry, Copilot Studio, large language models, embeddings, retrieval-augmented generation (RAG), and production workflow integrations. · Programming: Strong Python and SQL; comfortable with PySpark for large-scale data processing. · Data engineering fundamentals: ETL/ELT design, data modeling (dimensional & lakehouse/medallion), and building batch and streaming pipelines. · Ways of working: Comfortable with Agile delivery, with strong problem-solving skills and the ability to work independently across time zones and global teams.

 

What We Offer

~1 min read

 

 

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.  

 

This role may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

 

  • Medical, dental, vision
  • Annual employer HSA (Health Savings Account) funding for eligible employees who elect an HSA medical plan
  • STD, LTD, Basic Life AD&D coverage
  • 401k + employer matching
  • Vacation and Sick Time
  • 2 Volunteer Days off per year
  • Emergency evacuation time off
  • 11 paid company holidays
  • 1 Floating holiday to celebrate your birthday or important religious/holiday to you
  • Quarterly product allowance to use towards your favorite Metagenics products!
  • Product discount
  • Peer to peer recognition programs & more!

A minimum of three workdays per week are to be conducted at the Jersey City office (111 Town Square Pl, Jersey City, NJ 07310).

 

Learn more about how we help patient live happier and healthier lives here: https://www.metagenics.com/en-us/about-us

 

Metagenics, and its companies are committed to providing equal employment opportunity without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other protected status with respect to recruitment, hiring, promotion and other terms and conditions of employment. Metagenics takes affirmative action in support of this policy to employ and advance in employment individuals who are minorities, women, disabled, and veterans.

 

Click here for Metagenics’ California Data Privacy Act Disclosure

 

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Location & Eligibility

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Listing Details

Posted
October 8, 2026
First seen
October 9, 2026
Last seen
October 10, 2026

Posting Health

Days active
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Trust Level
49%
Scored at
October 10, 2026

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Data Engineer (AI Engineering)