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- Tasks: Design and optimise data pipelines for engineering and operational data.
- Company: Join a leading firm in the engineering and manufacturing sector.
- Benefits: Flexible hybrid work, competitive pay, and opportunities for professional growth.
- Other info: Collaborate with cross-functional teams and enhance your skills in a regulated industry.
- Why this job: Make an impact by working with cutting-edge data technologies in a dynamic environment.
- Qualifications: Experience in data engineering and proficiency with ETL/ELT processes.
The predicted salary is between 50000 - 65000 £ per year.
Proven experience as a Data Engineer working in engineering, manufacturing, or enterprise environments. Strong hands-on experience with ETL/ELT development across batch and streaming workloads. Skilled in building and maintaining data-streaming pipelines (e.g., Kafka, Spark Streaming, or equivalent). Proficiency with Databricks and Apache Spark for large-scale data processing. Experience with Hadoop and/or wider Apache ecosystem tools (e.g., Kafka, NiFi, Airflow). Strong understanding of Product Data Management (PDM), PLM, and/or engineering data structures. Experience integrating data from PDM, PLM, ERP, manufacturing, or other engineering systems. Hands-on experience with cloud data platforms (Azure Data Lake, Data Factory, Synapse, or similar). Ability to work with structured and unstructured engineering data across product lifecycle processes. Comfortable working in secure, regulated, and multi-national environments.
Key Responsibilities:
- Design, build, and optimise data ingestion, transformation, and integration pipelines.
- Implement scalable processing frameworks using Databricks, Spark, Hadoop, and Apache technologies.
- Develop and support real-time and near-real-time data-streaming pipelines for engineering and operational data.
- Integrate engineering datasets across PDM, PLM, ERP, manufacturing, and digital engineering platforms.
- Support modelling and structuring of engineering data in alignment with architectural guidance.
- Assist Data Architects with the implementation of data standards and data models (light ISO 10303 exposure where required).
- Develop data solutions aligned with defined architectural frameworks and security requirements.
- Ensure data quality, lineage, metadata, and governance practices are implemented in all pipelines.
- Collaborate with architects, engineering SMEs, and cross-functional teams to gather requirements and deliver robust data solutions.
Desirable Skills:
- Produce documentation, operational handover materials, and best-practice guidance.
- Troubleshoot, optimise, and maintain performance of cloud-based and distributed data systems.
- Experience with PLM platforms such as Siemens Teamcenter, Windchill, 3DX, or Aras.
- Exposure to ERP systems (SAP, Oracle, IFS, or equivalent).
- Familiarity with manufacturing systems (MES/MOM).
- Working knowledge of engineering data standards (e.g., ISO 10303 / STEP).
- Experience with data cataloguing, metadata management, lineage tools, or governance platforms.
- Understanding of engineering lifecycle processes, digital thread concepts, and systems engineering methodologies.
- Experience in large-scale defence, aerospace, or highly regulated engineering environments.
- Strong communication and stakeholder engagement skills.
Data Engineer in Reading employer: Stable
Contact Detail:
Stable Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Reading
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, attend meetups, and join relevant online communities. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ETL/ELT development or data-streaming pipelines. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with tools like Databricks, Spark, and cloud platforms. Practice common interview questions and scenarios related to data engineering.
✨Tip Number 4
Don't forget to apply through our website! We regularly update our job listings, and applying directly can sometimes give you an edge. Plus, it’s a great way to show your enthusiasm for joining our team!
We think you need these skills to ace Data Engineer in Reading
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with ETL/ELT development and any hands-on work with tools like Databricks and Apache Spark. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific projects where you've built or maintained data-streaming pipelines. If you've worked with Kafka or Spark Streaming, let us know! Real-world examples can really make your application stand out.
Be Clear and Concise: When writing your cover letter, keep it clear and to the point. Explain why you're a great fit for the role and how your experience aligns with our needs. We appreciate straightforward communication!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can't wait to see what you bring to the table!
How to prepare for a job interview at Stable
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Databricks, Spark, and Kafka. Brush up on your ETL/ELT processes and be ready to discuss how you've implemented these in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in data engineering roles. Think about how you optimised data pipelines or resolved issues with data quality. This will demonstrate your hands-on experience and critical thinking.
✨Understand the Business Context
Familiarise yourself with the company’s industry and how data engineering plays a role in their operations. Being able to connect your technical skills to their business needs will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions about the team, projects, and company culture. This shows your genuine interest in the role and helps you assess if it’s the right fit for you. Plus, it gives you a chance to engage with your interviewers.