Senior/Lead Data Engineer, Industrial Knowledge

This is a fully remote position, open to applicants in Poland.

📋 Description

• Design and develop ingestion and transformation pipelines from industrial source systems into organized, verifiable datasets.

• Collaborate directly with data from MES, SCADA, historians, PLC/OT systems, LIMS/LAB/OPS platforms, and various operational sources.

• Conduct data quality audits to identify: Anomalies, inactive or dead signals, data gaps, and inconsistencies.

• Create datasets and validation logic that support KPI definitions and the delivery of proof of concept (PoC) initiatives.

• Construct PoC components such as: Batch analytics pipelines, event detection logic, and time-series transformations.

• Develop lightweight PoC tools, dashboards, applications, or visualizations as needed.

• Assist presales and consulting teams by crafting technical solutions and uncovering business value within industrial data.

• Generate delivery-ready documentation, handover materials, and assets for implementation support.

⛳️ Requirements

• Over 5 years of experience in Data Engineering, industrial analytics, or data solution delivery.

• Proficient in Python and SQL for constructing ingestion pipelines, transformations, and validation logic.

• Demonstrated experience in developing reproducible, auditable, and scalable data products.

• Practical experience with industrial and operational data, including: MES, SCADA, historians, PLC/OT systems, and operational time-series data.

• Strong foundation in data profiling and data quality assessment, encompassing: Anomaly detection, gap analysis, dead signal analysis, and inconsistency checks.

• Capability to design datasets that are aligned with business KPIs and PoC goals.

• Robust engineering discipline: Git-based workflows, code reviews, testing practices, documentation, and runbooks.

• Experience in PoC-driven, KPI-focused project environments.

• English proficiency: B2 or higher.

🏝️ Benefits

• Comprehensive health and wellness programs.

• Opportunities for professional development and continuous learning.

• Flexible working arrangements to support work-life balance.

• Competitive salary and performance-based incentives.