Senior Lead Data Engineer with industrial knowledge Freelancer, REMOTE WROCŁAW

  • 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

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

Spyrosoft is an authentic, cutting-edge software engineering company, established in 2016. In 2021 and 2022, we were among the fastest growing technology companies in Europe, according to the Financial Times. We were founded by a group of tech experts with established backgrounds in software engineering, who created an ‘engineer-to-engineer’ workplace, powered by enthusiasm, fairness and authentic relationships. Having a unique offering, which bridge the gap between technology and business, we specialise in technology solutions for industry 4.0, automotive, geospatial, healthcare & life sciences, employee experience & education and financial services industries.

,[Design and implement ingestion and transformation pipelines from industrial source systems into clean, auditable datasets, Work directly with data from MES, SCADA, historians, PLC/OT systems, LIMS/LAB/OPS platforms, and other operational sources, Perform data quality audits and identify:, Anomalies, Dead or inactive signals, Data gaps, Inconsistencies, Develop datasets and validation logic supporting KPI definitions and PoC delivery, Build PoC components such as:, Batch analytics pipelines, Event detection logic, Time-series transformations, Create lightweight PoC tooling, dashboards, applications, or visualizations when required, Support presales and consulting teams by shaping technical solutions and identifying business value hidden in industrial data, Produce delivery-grade documentation, handover materials, and implementation support assets] Requirements: Data engineering, Python, SQL, MES, SCADA, PLC, Databricks, Apache Spark, Snowflake, Cloud, AWS, Data models, Use cases, AI
Data publikacji: 2026-06-05
APLIKUJ