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- Tasks: Analyse telemetry and sensor data to uncover trends and insights for engineering teams.
- Company: Join a leading aerospace engineering firm focused on innovation and technology.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make a real impact by transforming complex data into actionable insights.
- Qualifications: Experience in data analysis, familiarity with statistical techniques, and strong communication skills.
- Other info: Collaborative environment with exciting projects and career advancement potential.
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 Reading employer: Stable
Contact Detail:
Stable Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst - Telemetry & Engineering Data in Reading
✨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 be shy about asking for informational interviews. We all know that sometimes it’s not just what you know, but who you know!
✨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, and we love seeing creativity in action!
✨Tip Number 3
Prepare for interviews by brushing up on common statistical techniques and data visualisation tools like Power BI or Tableau. Practice explaining complex concepts in simple terms, as you’ll need to communicate insights clearly to non-data specialists. We want you to shine during those interviews!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we often have exclusive opportunities listed there. So, keep an eye out and get your applications in!
We think you need these skills to ace Data Analyst - Telemetry & Engineering Data in Reading
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data analysis, especially with telemetry or sensor data. We want to see how your skills align with the role, so don’t be shy about showcasing your analytical prowess!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data analysis in an aerospace context and how your background makes you a great fit for our team. Keep it engaging and personal!
Showcase Your Technical Skills: We love seeing candidates who are comfortable with tools like Power BI, Tableau, and Python. Make sure to mention any relevant projects or experiences that demonstrate your ability to analyse and visualise data effectively.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
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 genuine interest and expertise.
✨Brush Up on Statistical Techniques
Make sure you have a solid understanding of key statistical methods like correlation analysis and regression analysis. Be prepared to explain how you would apply these techniques to real-world scenarios, especially in an aerospace context. This will demonstrate your analytical awareness and practical skills.
✨Showcase Your Dashboard Skills
Since presenting insights through dashboards is crucial, be ready to discuss your experience with tools like Power BI or Tableau. Bring examples of dashboards you've created and explain how they helped stakeholders understand complex data. This will highlight your ability to communicate insights clearly.
✨Engage with Stakeholders
The role involves working closely with engineering teams, so practice how you would translate technical questions into analytical approaches. Think of examples where you've successfully communicated complex data insights to non-data specialists. This will showcase your stakeholder engagement skills.