At a Glance
- Tasks: Design and implement data solutions that drive innovation in aerospace and defence.
- Company: Join a leading aerospace company focused on cutting-edge data engineering.
- Benefits: Enjoy a competitive salary, generous pension contributions, and flexible working arrangements.
- Other info: Dynamic work environment with opportunities for career growth and professional development.
- Why this job: Make a real impact by transforming data into actionable insights for strategic decisions.
- Qualifications: Experience in data engineering with strong skills in Python, SQL, and ETL tools.
The predicted salary is between 63000 - 77000 £ per year.
In this role you design enterprise-wide data and BI solutions by integrating diverse data sources from simulators, test systems, and production environments to create governed, value-generating data assets. You will work across engineering, simulation, production, quality, and corporate functions to deliver end-to-end data solutions and drive DataOps in hybrid/on-prem settings. This position blends advanced analytics with compliance to defence requirements, offering impact across multiple directorates. You will collaborate with cross-functional teams to transform data into actionable insight and strategic decision support.
Key Responsibilities:
- Capture needs and deliver end-to-end data solutions across technical and business domains.
- Build scalable ETL/ELT and streaming pipelines from simulators, HIL/SIL benches, MES/SCADA, ERP, and PLM.
- Architect data lakes, warehouses, lakehouses, and time-series stores.
- Develop Power BI analytics for self-service, KPI monitoring, and executive reporting.
- Define data models, governance, quality, lineage, and security aligned with defence requirements (ITAR/EAR, cybersecurity).
- Drive DataOps: CI/CD, monitoring, CaaS (Container as a Service) integration model on hybrid/on-prem environments.
Experience:
- Experience in data engineering, ideally aerospace/defence or industrial sectors.
- ETL/ELT tools (Airflow, Azure, Microsoft SSIS).
- Streaming (Spark, Kafka).
- Strong Python and SQL; C++, C#, or MATLAB a plus.
- Databases: PostgreSQL, SQL Server, Oracle, Snowflake, Iceberg, TimescaleDB.
- Data Platform Capabilities: Low-Code No-Code Data Science solutions (Dataiku, Knime), Data Virtualisation (Dataiku, Ab Initio, Starburst), Data Visualisation (Power BI, DAX, Tableau).
- T/OT integration, Industry 4.0.
- DevOps/DataOps: Git, Docker, Kubernetes, CI/CD.
- Aware of DO-178C, ISO 27001, MOD guidelines appreciated.
Key Requirements:
- Bonus up to £2,500.
- Pension contributions up to 14%.
- Overtime opportunities.
- Flexi Leave up to 15 days.
- Flexible working arrangements.
- Enhanced parental leave up to 26 weeks.
Senior Data Engineer in Bolton employer: MBDA S.A.S.
At MBDA S.A.S., we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of Bolton. Our commitment to employee growth is evident through our comprehensive training programmes and opportunities for advancement, alongside competitive salaries and flexible working options that ensure a healthy work-life balance. Join us to be part of a forward-thinking team where your contributions are valued and rewarded.
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We think this is how you could land Senior Data Engineer in Bolton
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We think you need these skills to ace Senior Data Engineer in Bolton
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at MBDA S.A.S.
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at MBDA S.A.S.!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
