Role Purpose

The Process Automation & Data Integration Engineer is responsible for connecting systems, automating business and operational processes, and enabling data-driven decision-making across the organization.

The role focuses on hands-on implementation and orchestration, not on replacing core systems such as ERP, SCADA, or future MES. Instead, this position acts as an in-house integration layer, ensuring that data from production, equipment, finance, HR, and administration is accessible, reliable, and usable through automation, BI dashboards, and AI-assisted workflows.

This role forms the technical foundation for scalable digitalization, advanced analytics, and future MES integration.

Key Responsibilities

1. Process Automation & Workflow Orchestration

Design, implement, and maintain automation workflows for administrative and operational processes (e.g. invoice processing, approval flows, reporting, HR workflows).
Combine low-code automation platforms (e.g. n8n, Power Automate or similar) with custom scripting (Python, JavaScript) where required.
Ensure automation reliability through proper error handling, logging, retries, and monitoring.
Continuously improve existing workflows as business processes evolve.

2. Data Integration & Lightweight ETL

Connect to enterprise systems (e.g. ERP such as SAP) via APIs, OData, connectors, or database access.
Design and maintain internal SQL-based data models for analytical and operational use.
Build and operate automated ETL pipelines (extract, transform, load) with scheduled refreshes and data quality controls.
Establish a unified and well-documented data structure across production, finance, HR, logistics, and other functions.

3. BI & Analytical Enablement

Build and maintain BI dashboards that link operational data with business KPIs.
Support production, finance, HR, and management teams with accurate and timely reporting.
Ensure automated data refresh, consistency, and traceability of metrics.
Quickly respond to ad-hoc analytical and reporting requests.

4. Equipment Data Integration (Industrial Context)

Coordinate with equipment vendors and automation teams to understand available data interfaces and communication protocols.
Implement data collection pipelines for selected equipment and systems (e.g. climate control, furnaces, mixers, process sensors).
Stream near real-time or high-frequency data into internal databases where required.
Implement basic alerting and monitoring logic for deviations from expected operational ranges.

Note: This role does not replace PLC or SCADA engineering, but ensures data availability and usability for IT and analytics purposes.

5. AI-Assisted Automation & Digital Enablement

Implement AI-assisted workflows such as:
document classification and extraction (e.g. invoices from email)
intelligent routing and approval workflows
Integrate AI components into existing automation pipelines to improve efficiency and data quality.
Support experimentation and gradual rollout of AI-based agents within business processes.

6. Internal Enablement & Cross-Team Collaboration

Act as the internal technical point of contact for automation, integration, and data-related topics.
Collaborate with business teams to translate needs into technical solutions.
Coordinate with external vendors and system integrators for large or specialized projects.
Provide basic documentation and user guidance for internal tools and dashboards.

Required Competencies & Skills

Core Skills

Solid SQL knowledge, including data modeling, relationships, indexing, and performance considerations.
Experience with automation and scripting:
Python, JavaScript, or similar
low-code / workflow automation platforms (e.g. Power Automate, n8n, UiPath or similar).
Hands-on experience building system integrations via APIs, OData, databases, and file-based interfaces.
Experience designing and maintaining lightweight ETL pipelines.
Practical experience with BI tools (e.g. Power BI, Looker, Metabase, Tableau).

Nice to Have

Basic understanding of industrial and manufacturing environments.
Familiarity with PLC-related concepts and protocols (e.g. OPC UA, Modbus) at a conceptual level.
Experience integrating equipment or telemetry data into IT systems.
Exposure to AI-assisted automation or LLM-based workflows.

Personal Attributes

High level of ownership and responsibility.
Strong attention to data accuracy and process reliability.
Ability to work independently across multiple systems and domains.

Systems thinking and the ability to translate business needs into technical solutions.