Senior/ Lead Data Engineer with industrial knowledge (Freelancer)
We are looking for a Senior / Lead Data Engineer (Freelance) to join project-based initiatives focused on industrial data and AI-driven analytics within the chemical and process industry.
Engagement model:
✅Freelance cooperation
✅Part-time or full-time involvement
✅Sequential project-based work
✅Hourly salary: 140 - 200 PLN
The cooperation model is flexible and based on short- to mid-term contracts, typically connected to KPI-driven Proof of Concepts (PoCs) and industrial analytics initiatives. Projects usually last 3-8 weeks, with new opportunities appearing every 1-2 months.
About the role:
You will work with real industrial and production data, supporting digitalization initiatives that directly impact measurable business outcomes. The role combines hands-on data engineering with early-stage solution design and close cooperation with consulting and presales teams.
Why Is It Worth Joining Us?
🔥 Why join our Chemical Industry Software Engineering team?
➡️ You will work on real industrial and manufacturing data challenges within the chemical industry
➡️ You will help shape PoC initiatives that directly influence measurable business outcomes
➡️ You’ll gain exposure to industrial analytics, operational time-series data, and AI-driven use cases
➡️ You’ll collaborate with engineers and consultants experienced in OT systems, industrial operations, and scalable data platforms
➡️ You will have direct influence on technical approaches, data validation strategies, and solution design during early project phase
Tech stack:
- Python
- SQL
- Databricks / Apache Spark
- Snowflake / Lakehouse architectures
- AWS or Azure
- Streamlit, Plotly, Power BI
- Industrial data sources: MES, SCADA, Historians, PLC/OT, LIMS, ELN
About Spyrosoft
- 5+ years of experience in Data Engineering, industrial analytics, or data solution delivery
- Strong Python and SQL skills for building ingestion pipelines, transformations, and validation logic
- Proven experience in building reproducible, auditable, and scalable data products
- Hands-on experience with industrial and operational data, including: MES, SCADA, Historians, PLC / OT systems, Operational time-series data
- Solid background in data profiling and data quality assessment, including: (Anomaly detection, Gap analysis, Dead signal analysis, Inconsistency checks)
- Ability to design datasets aligned with business KPIs and PoC objectives
- Strong engineering discipline (Git-based workflows, Code reviews, Testing practices, Documentation and runbooks)
- Experience working in PoC-driven, KPI-oriented project environments
- English level: B2 or higher
- Experienced in using AI tools in day-to-day engineering workflows
Nice to have:
- Experience with Databricks, Apache Spark, Snowflake, or lakehouse platforms
- Familiarity with cloud environments (AWS and/or Azure)
- Experience building PoC tooling or visualizations using Streamlit, Plotly, or Power BI
- Understanding of industrial / OT environments and historian-based data models
- Exposure to analytics or ML use cases in:
Manufacturing
- Process industry
- Energy
- Chemical or Pharma sectors