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- Tasks: Analyse telemetry data and present insights through engaging dashboards.
- Company: Join a leading aerospace engineering team focused on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make an impact by transforming complex data into actionable insights.
- Qualifications: Experience in data analysis and familiarity with statistical techniques.
- Other info: Collaborative environment with exciting projects in aerospace technology.
The predicted salary is between 35000 - 45000 £ per year.
The Data Analyst will support engineering and operational teams by analysing telemetry and sensor data generated from complex engineering systems. The role involves identifying trends, correlations, and anomalies across operational datasets and presenting insights through dashboards and visualisations.
While the role sits within an aerospace engineering environment, experience analysing telemetry or sensor data from manufacturing, industrial systems, industrial IoT, or other engineering domains is highly relevant. The focus is on practical data analysis, statistical awareness, and communicating insights clearly through dashboards.
Key Responsibilities- Analyse telemetry and operational datasets generated by complex engineering systems.
- Identify trends, correlations, and anomalies across performance metrics.
- Support engineers and operational teams in investigating performance questions using data-driven analysis.
- Work with large datasets representing system performance over time.
- Example datasets may include:
- Equipment performance telemetry
- Sensor readings from industrial systems
- Operational metrics from manufacturing equipment
- Environmental and system performance data (in the aerospace context this may include engine, airframe, or flight sensor data).
The analyst should have an awareness of common statistical approaches used in engineering data analysis, including:
- Correlation Analysis: Identifying relationships between variables to understand how different operational parameters move together.
- Regression Analysis: Used to understand how one or more variables influence a particular outcome or performance metric.
- Time Series Analysis: Analysing data over time to identify trends, drift, cyclic behaviour, or performance degradation.
- Bayesian Approaches (Awareness): Understanding how new observations can update probabilities or expectations based on prior knowledge.
- Basic Anomaly Detection: Identifying unusual patterns in telemetry or sensor data that may indicate faults or abnormal system behaviour.
The role requires awareness of these techniques and when to apply them, rather than deep academic statistical expertise.
Dashboarding & Data VisualisationA key deliverable for the role is presenting insights clearly through dashboards. The analyst should be able to:
- Build dashboards using Power BI or Tableau
- Visualise operational and telemetry trends
- Provide engineers and stakeholders with clear views of system performance
- Enable drill-down investigation of anomalies or trends.
Typical technologies may include:
- Microsoft / Azure data stack
- Azure Data Lake
- Azure Databricks
- Azure Synapse
- Azure Data Factory
- Data analysis: Python (Pandas / NumPy), SQL
- Visualisation: Power BI or Tableau
The role requires working closely with engineering and operational stakeholders. The analyst should be able to:
- Ask informed questions about system behaviour and operational context
- Translate engineering questions into analytical approaches
- Communicate insights clearly to non-data specialists.
Candidates should demonstrate awareness of common pitfalls such as:
- Confusing correlation with causation
- Interpreting noisy sensor data incorrectly
- Drawing conclusions from incomplete datasets
- Overfitting analytical models.
Candidates may come from environments such as:
- Manufacturing data analytics
- Industrial IoT or sensor data analytics
- Engineering or operational data analysis
- Reliability or predictive maintenance analytics
- Aerospace or defence analytics.
Data Analyst - Telemetry & Engineering Data in Slough employer: Stable
Contact Detail:
Stable Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst - Telemetry & Engineering Data in Slough
✨Tip Number 1
Network like a pro! Reach out to professionals in the aerospace and engineering sectors on LinkedIn. Join relevant groups, participate in discussions, and don’t hesitate to ask for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those involving telemetry or sensor data. Use platforms like GitHub to share your code and visualisations. This gives potential employers a taste of what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on common statistical techniques and data visualisation tools like Power BI or Tableau. Be ready to discuss how you've used these in past projects. Practice explaining complex data insights in simple terms – it’s all about clear communication!
✨Tip Number 4
Don’t just apply anywhere; apply through our website! Tailor your application to highlight your experience with operational datasets and your analytical awareness. Make sure to connect your skills to the specific requirements of the Data Analyst role – we want to see how you fit!
We think you need these skills to ace Data Analyst - Telemetry & Engineering Data in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience with telemetry and sensor data. We want to see how your skills align with the role, so don’t be shy about showcasing your analytical prowess!
Showcase Your Dashboard Skills: Since presenting insights through dashboards is key, include examples of dashboards you've built using Power BI or Tableau. We love seeing how you can visualise data trends and make complex info digestible!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, especially when it comes to communicating insights. Avoid jargon unless it’s necessary, and make sure your points are easy to follow.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Stable
✨Know Your Data Inside Out
Before the interview, dive deep into the types of telemetry and sensor data relevant to the role. Familiarise yourself with examples like equipment performance telemetry and environmental data. Being able to discuss specific datasets and their implications will show your understanding and enthusiasm for the position.
✨Brush Up on Statistical Techniques
Make sure you have a solid grasp of key statistical methods such as correlation analysis and regression analysis. Be prepared to explain how these techniques can be applied to real-world scenarios in aerospace engineering. This will demonstrate your analytical skills and readiness to tackle the challenges of the role.
✨Showcase Your Dashboard Skills
If you have experience with Power BI or Tableau, bring examples of dashboards you've created. Discuss how you visualised data trends and insights. This practical demonstration of your skills will help you stand out, as presenting data clearly is a crucial part of the job.
✨Engage with Stakeholders
Prepare to discuss how you would interact with engineering and operational teams. Think about how you would translate complex data insights into actionable recommendations for non-data specialists. Showing that you can communicate effectively will highlight your ability to work collaboratively in the role.