IT/OT Data Engineer

Merz North America•Racine, WI

About The Position

Founded in 1908, Merz is a successful, family-owned specialty healthcare company with a rich history. As a leading global aesthetics business, our award-winning portfolio of injectables, devices, and skincare products empowers healthcare professionals to enhance confidence through aesthetic medicine. Our purpose is to fuel confidence by helping people look better, feel better, and live better. We believe you do not have to choose between living life and making a living. Live your best life with Merz Aesthetics. A Brief Overview As the organization's initial data engineering hire, this position will develop and support reliable OT to MES/UNS pipelines, integrate enterprise applications (ERP, QMS, complaints) through REST/SOAP APIs, and help establish repeatable integration practices for the data platform. Furthermore, they will collaborate with the first data scientist to build and maintain the organization's digital backbone.

Requirements

Bachelor's Degree Data Engineering or Computer Science
3-5 years of data engineering and/or systems integration, with strong exposure to industrial/OT data or high-throughput production systems
3-5 years of hands-on experience with OPC UA, AMQP and SCADA gateways.
3-5 years working with REST/SOAP APIs, schema evolution, and CDC patterns.
2+ years working in GxP environments with awareness of CSV expectations.
Build/operate batch & streaming pipelines; performance tuning, backpressure handling, and idempotency.
Tooling familiarity (e.g., Spark/Databricks/Synapse, Event Hubs/Kafka/IoT Hub or equivalent).
Protocol familiarity (i.e. OPC UA, MQTT, AMQP, REST/SOAP, file/EDI).
API design/consumption: pagination, throttling, OAuth/SAML/SAS, bulk loads, file drops with integrity checks.
Translating ambiguous business needs into clear data contracts, SLAs, and acceptance criteria.
Strong Python and SQL; Git-based workflows; CI/CD (e.g., GitHub Actions, Azure DevOps).
Proficiency with streaming and batch paradigms (e.g., Kafka/Event Hubs/IoT Hub, or equivalents).
Good knowledge about organization standards, processes and customers, capability to expand this knowledge
Ability to work with moderate guidance
Ability to resolve problems by applying prescribed guidelines and policies
Ability to explain complex information effectively & and support others in straight forward tasks
Good MS Office package skills & familiarity with the most common AV technology

Nice To Haves

Experience integrating MES, ERP, QMS, lab equipment and SCADA.
Experience working with Ignition, Litmus, and Fuuz.
Experience working with prompt engineering large language models.

Responsibilities

Design, implement, and operate reliable batch and streaming pipelines from OT and enterprise systems to the UNS and analytics platforms.
Implement event/streaming ingestion (e.g., MQTT, Kafka/Azure Event Hubs) and high-throughput batch workflows, ensuring performance, scalability, and maintainability.
Connect laboratory and shop-floor equipment to MES, ELN, LIMS and/or the UNS (e.g., OPC UA servers, Kepware, Ignition, industrial gateways).
Integrate enterprise applications via REST/SOAP APIs, file drops/EDI, and CDC/connectors (e.g., ERP, QMS, CRM, complaints), with appropriate data contracts and versioning.
Build Infrastructure-as-Code (IaC) environments and implement CI/CD for data pipelines, including automated unit, integration, and data quality testing.
Establish observability (logging, metrics, tracing), define SLAs/SLOs/SLIs, and author runbooks to support on-call operations and continuous improvement.
Enforce least-privilege access, OT/IT network segmentation (including DMZ patterns), and secure secrets management.
Collaborate on CSV/GAMP 5 deliverables and ensure audit trails and change controls aligned to 21 CFR Part 11.
Partner with data science and cross-functional stakeholders to define and maintain data contracts, schemas, and naming conventions.
Develop reusable connectors, templates, and documentation to accelerate future integrations and promote consistency.