Asset Analytics Engineer

Capgemini Engineering; Województwo pomorskie; Hybrid; PLN 180,000 - 300,000; Full time

Job summary

Capgemini Engineering seeks an Asset Analytics Engineer to own end-to-end deployment of predictive models for industrial asset fleets, leveraging platforms like SmartSignal, Aspen Mtell, and AVEVA PRiSM. You will transform historian data into high-fidelity digital twins to support reliability decisions.

The role requires strong Python (Pandas, NumPy) and SQL skills, experience with PI/OPC/IP21 historians, and a structured approach to data quality and governance.

Qualifications

• 5+ years of experience in data analytics, reliability engineering, or a related field, with hands-on experience on platforms such as SmartSignal, Aspen Mtell, or AVEVA PRiSM, including Blueprint and model review workflows
• Strong Python proficiency (Pandas, NumPy) for data manipulation and custom analytics development, combined with solid SQL skills for querying CMMS systems (Maximo, SAP PM) and Historian database
• Demonstrated experience with industrial data systems including PI, OPC, and IP21 historians, and familiarity with API data extraction tools such as Postman or equivalent
• A structured, detail-oriented approach to data quality and model governance, with the ability to manage model lifecycle activities including training, tuning, retraining, and performance monitoring across large asset fleets

Responsibilities

• Performing complextag mapping of historian data sources (PI, OPC, IP21) to the SmartSignal Standard Data Model, ensuring data lineage, quality, and consistency across fleet-level deployment
• Applying SBM and EML techniques to establish accurate 'Normal' operating profiles, selecting Gold Standard training windows that represent healthy asset state
• Developing and maintaining Analytic Blueprints—reusable templates for common industrial asset classes such as pumps, motors, and transformers - to enable rapid and scalable deployment
• Monitoring model performance using Precision/Recall metrics, performing retraining following asset overhauls, and tuning statistical thresholds to minimise false positives and maximise signal fidelity
• Writing Python scripts(Pandas, NumPy) for data manipulation, custom analytic rule development, and feature engineering to enhance model accuracy

Skills

Python (Pandas, NumPy)

SQL

Data analytics

Reliability engineering

Tools

SmartSignal

Aspen Mtell

AVEVA PRiSM

Maximo

SAP PM

PI/OPC/IP21 historians

Postman

Job description

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s mostinnovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as theyprovide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days arethe same.

Your role

As anAsset Analytics Engineerwith a focus on Smart Signal and Predictive Modelling, you will take ownership of the end-to-end technical deployment of predictive models across industrial asset fleets. Leveraging platforms such as SmartSignal (GE Vernova), Aspen Mtell, or AVEVA PRiSM, you will transform raw historian data into high-fidelity digital twins that power reliability decisions.

Your tasks

• Performing complextag mappingof historian data sources (PI, OPC, IP21) to the SmartSignal Standard Data Model, ensuring data lineage, quality, and consistency across fleet-level deployment
• ApplyingSimilarity-Based Modelling (SBM)andEmpirical Model Learning (EML)techniques to establish accurate 'Normal' operating profiles, selecting Gold Standard training windows that represent healthy asset state
• Developing and maintainingAnalytic Blueprints- reusable templates for common industrial asset classes such as pumps, motors, and transformers - to enable rapid and scalable deployment
• Monitoring model performance usingPrecision/Recall metrics, performing retraining following asset overhauls, and tuning statistical thresholds to minimise false positives and maximise signal fidelity
• WritingPython scripts(Pandas, NumPy) for data manipulation, custom analytic rule development, and feature engineering to enhance model accuracy

Your profile

• 5+ years of experiencein data analytics, reliability engineering, or a related field, with hands-on experience on platforms such as SmartSignal, Aspen Mtell, or AVEVA PRiSM, including Blueprint and model review workflows
• StrongPython proficiency(Pandas, NumPy) for data manipulation and custom analytics development, combined with solidSQL skills for querying CMMS systems (Maximo, SAP PM) and Historian database
• Demonstrated experience withindustrial data systemsincluding PI, OPC, and IP21 historians, and familiarity with API data extraction tools such as Postman or equivalent
• A structured, detail-oriented approach todata quality and model governance, with the ability to manage model lifecycle activities including training, tuning, retraining, and performance monitoring across large asset fleets

What You'll Love About Working Here

• Well-being culture:medical care with Medicover, private life insurance, and sports card. But we went one step further by creating our own Capgemini Helpline offering therapeutical support if needed and the educational podcast 'Let's talk about wellbeing' which you can listen to on Spotify.
• Access to over 70 training trackswith certification opportunities (e.g., GenAI, Architects, Google) on our NEXT platform. Dive into a world of knowledge with free access to Education First languages platform, TED Talks and Udemy Business materials and trainings.
• Continuous feedback and ongoing performance discussions thanks to our performance management tool GetSuccess supported by a transparent performance management policy.
• Enjoy hybrid working modelthat fits your life - after completing onboarding, connect work from a modern office with ergonomic work from home, thanks to home office package (including laptop, monitor, and chair). Ask your recruiter about the details.

Get to know us

Capgemini is committed to diversity and inclusion, ensuring fairness in all employment practices. We evaluate individuals based on qualifications and performance, not personal characteristics, striving to create a workplace where everyone can succeed and feel valued.

Do you want to get to know us better? Check our Instagram — @capgeminipl or visit our Facebook profile — Capgemini Polska. You can also find us on YouTube.

About Capgemini

Capgemini is the business transformation partner for enterprises in the age of AI. We help organizations imagine and build an intelligent, sustainable future, combining AI, technology and human ingenuity to transform how they operate, innovate and grow. With unique end-to-end capabilities spanning strategy, technology, engineering and intelligent operations, we bring together deep industry expertise and market-leading capabilities in AI, cloud and data to turn ambition into measurable business outcomes at scale. Supported by a robust ecosystem of partners and nearly 60 years of expertise, Capgemini is a responsible and diverse global organization of over 410,000 team members in more than 50 countries. The Group reported 2025 revenues of €22.5 billion.

Make it real | www.capgemini.com