At a Glance
- Tasks: Create reliable data solutions for the rail industry using Python and SQL.
- Company: Join a leading organisation supporting rail safety and performance through innovative data solutions.
- Benefits: Enjoy 30 days annual leave, private medical cover, and a performance-related bonus.
- Other info: Flexible working options and excellent career development opportunities await you.
- Why this job: Make a real impact in the rail industry while developing your technical skills.
- Qualifications: BSc in a relevant field with experience in data analysis and Python.
The predicted salary is between 63000 - 77000 £ per year.
Описание
RSSB supports the rail industry through data, standards, and digital products focused on health, safety, quality, operational performance, and sustainability.
Its data solutions integrate national, industry, and internal business sources to support analytics, decision-making, and business processes.
- Задачи
- Ensure data for downstream applications is reliable, accessible, and appropriately formatted through engagement with Product Management and stakeholders
- Plan and drive the development of data solutions while balancing functional and non-functional requirements
- Advise on approaches to novel data problems using Python-based solutions
- Apply data standards and architectures to deliver reliable and well-engineered solutions
- Conduct complex data quality checks and monitoring, and perform remediation to maintain data integrity
- Maintain and optimise data pipelines, APIs, and applications for performance and reliability
- Develop quick prototypes and high-quality products according to the context
- Design, code, test, and document complex data engineering scripts and applications using SQL, Python, and software engineering best practices
- Collaborate with Product Management and stakeholders to understand business requirements and translate them into technical solutions
- Communicate technical concepts and solutions to technical and non-technical audiences
- Mentor and coach colleagues on problem-solving approaches and deliverable quality
- Требования
- Hold a BSc in a scientific, computer science, or related discipline
- Have extensive experience with data analysis, data modelling, and quality assurance techniques
- Proficiency in SQL and Python
- Experience developing Python data pipelines with orchestrators such as Airflow
- Experience making data available in data science and data visualisation tools such as Databricks and Power BI/Fabric
- Experience extracting data from various systems, including familiarity with web-oriented architecture
- Ability to analyse and document technical solutions effectively
- Communicate effectively and share ideas with audiences using appropriate methods
- Adapt effectively to new opportunities, change, and uncertainty
- Contribute actively to team goals and outcomes
- Take responsibility and accountability for completing tasks and achieving objectives
- Resolve problems and identify opportunities proactively
- Demonstrate commitment to customer service and customer satisfaction
- Collaborate within an evolving industry and build stakeholder confidence through subject-matter expertise
- Make timely and informed decisions while considering benefits and constraints
- Nice to have: Experience developing and deploying Python APIs with frameworks such as Fast API, familiarity with AWS, Azure, or GCP, experience with Git-based version control and repositories such as Azure Dev Ops Repos or Git Hub, experience with Microsoft SQL Server or Postgre SQL including query optimisation and performance tuning
- Условия
- 30 Days annual leave plus bank holidays
- Private medical and dental cover
- Season ticket loan and travel subsidy
- Cycle to work scheme
- Volunteer leave
- Performance-related bonus
- Pension scheme
- Learning and development opportunities
- Core hours with the option to vary the working location between the office and home
- Permanent role based at the Fenchurch Avenue office
- #J-18808-Ljbffr
data engineer for rail industry in London employer: Enfint
AJ Bell is an exceptional employer that fosters a collaborative and innovative work culture in the heart of London. With a strong emphasis on employee growth, you will have the opportunity to mentor junior designers while working on impactful design systems that prioritise accessibility and usability. Enjoy a supportive environment that values proactive communication and offers unique benefits tailored to enhance your professional journey.
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We think this is how you could land data engineer for rail industry in London
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We think you need these skills to ace data engineer for rail industry in London
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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Craft a Tailored Cover Letter:For a full-time role at Enfint, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Enfint. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Enfint
✨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!
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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
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✨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.
