At a Glance
- Tasks: Lead data engineering pipelines and manage a team to optimise our Lakehouse platform.
- Company: Join BMS Group, a dynamic company focused on innovative data solutions in London.
- Benefits: Enjoy a collaborative work environment with opportunities for skill development and career growth.
- Other info: This is a 12-month fixed-term contract with potential for future opportunities.
- Why this job: Be part of a cutting-edge team shaping the future of data engineering in a supportive culture.
- Qualifications: Experience as a lead Data Engineer with skills in SQL, Python, and Azure Databricks required.
The predicted salary is between 48000 - 72000 € per year.
BMS Group City Of London, England, United KingdomBMS Group City Of London, England, United KingdomReports to: Head of Data PlatformsLocation: LondonAbout the Role:We are seeking a highly motivated and skilled Senior Data Engineer to join our growing Data Platforms team at BMS Group. In this role, you will play a pivotal role in supporting BMS's ambition to fully realise the benefits of a Lakehouse platform deployed within Azure. Working under the Head of Data Platforms you will help manage, and implement the data engineering pipelines within Azure to ingest, enrich, and curate our; structured, semi-structured and unstructured data from our global business. In this role you will help lead a small team of engineers who you will be responsible for developing to support the business objectives of delivering a scalable and efficient platform for the business.Key Responsibilities:Responsible for owning and managing all data engineering pipelines and layers of the Lakehouse platform.Responsible for managing the prioritisation of data engineering backlog.Responsible for managing the peer review and testing process of any pipeline releases.Continuously engage with Head of Data Platforms, Group Head of Data Strategy and Governance and Architecture to understand the evolving needs of the business so that they can be supported by the Lakehouse platform.Own, with the support of Head of Data Platforms, the definition of standards and best practices for BMS's data engineering pipelines in relation to; code as well as documentation.Continuously monitor and analyse pipelines to identify opportunities for optimisation and efficiencies.Work within plan-driven (Waterfall) or iterative (Agile) delivery methodologies based on project requirements.Continuously learn and develop your skills to stay ahead of the curve in the evolving data landscape.Develop and implement generalised data engineering pipelines, based on patterns, to create efficient, scalable, and manageable pipelines.Collaborate with other central IT functions to ensure that the necessary access to systems and technology is granted based on the evolving needs of the team.Build a comprehensive understanding of both technical and business domains.Collaborate with cross-functional teams to understand and address data engineering and data needs.Knowledge and Skills:Experience working as a principal/lead Data Engineer.Experience working with large data sets and proficiency in SQL, Python and PySpark.Experience manging a team of engineers with varying levels of experience within data engineering.Experience deploying pipelines within Azure Databricks in line with the medallion architecture framework.Experience using SQL, Python and PySpark to build data engineering pipelines.Understanding of how to define best practices in relation to documentation standards as well as code standards.Understanding of data modelling approaches and standardsUnderstanding of semantic modelling techniques and how data is consumed from a Lakehouse to support them.Excellent communication and problem-solving skills.Experience working within an agile environment.Assist with the upskilling and continued improvement of junior members of the teamDesired skills and experience:Experience in the London Insurance Market, or the wider Financial Services sectorExperience building and deploying machine learning pipelines into data engineering pipelines.Experience of using metadata driven data engineering approaches for ingestion and transformations within data pipelines.Success Metrics:Manage and maintain high-quality and efficient data engineering pipelines to meet the technical requirements of the business.Share knowledge and expertise to develop and upskill your team to become better and more effective data engineers.Contribute to our team culture by creating a positively challenging environment.Seniority level Seniority level Mid-Senior levelEmployment type Employment type ContractJob function Job function Information TechnologyIndustries Insurance, Financial Services, and Information ServicesReferrals increase your chances of interviewing at BMS Group by 2xSign in to set job alerts for "Senior Data Engineer" roles. 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Senior Data Engineer - 12 Month FTC in London employer: BMS Group
BMS Group is an exceptional employer, offering a dynamic work environment in the heart of London where innovation and collaboration thrive. As a Senior Data Engineer, you will not only lead a talented team but also have access to continuous learning opportunities and the chance to shape the future of our data platforms. With a strong focus on employee development and a culture that encourages creativity and problem-solving, BMS Group stands out as a rewarding place to advance your career in data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - 12 Month FTC in London
✨Tip Number 1
Familiarise yourself with Azure Databricks and the medallion architecture framework. Understanding these technologies will not only help you in interviews but also demonstrate your commitment to the role and its requirements.
✨Tip Number 2
Showcase your leadership skills by preparing examples of how you've successfully managed a team of engineers. Highlight specific instances where you’ve upskilled junior members or improved team performance, as this is crucial for the role.
✨Tip Number 3
Engage with the London Insurance Market or Financial Services sector through networking events or online forums. This will give you insights into industry-specific challenges and trends, making you a more attractive candidate.
✨Tip Number 4
Brush up on your SQL, Python, and PySpark skills by working on personal projects or contributing to open-source initiatives. Practical experience will not only enhance your technical abilities but also provide concrete examples to discuss during interviews.
We think you need these skills to ace Senior Data Engineer - 12 Month FTC in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience as a Data Engineer, particularly with Azure, SQL, Python, and PySpark. Emphasise any leadership roles you've held and your experience managing teams.
Craft a Compelling Cover Letter:In your cover letter, express your enthusiasm for the role and the company. Discuss how your skills align with the responsibilities outlined in the job description, especially your experience with data engineering pipelines and team management.
Showcase Relevant Projects:If you have worked on specific projects that demonstrate your ability to manage data engineering pipelines or lead a team, include these in your application. Use metrics to showcase your impact where possible.
Highlight Continuous Learning:Mention any recent courses, certifications, or self-study related to data engineering, Azure, or leadership. This shows your commitment to staying current in the evolving data landscape, which is crucial for this role.
How to prepare for a job interview at BMS Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Python, and PySpark in detail. Highlight specific projects where you've successfully built data engineering pipelines, especially within Azure Databricks, as this will demonstrate your technical proficiency.
✨Demonstrate Leadership Experience
Since the role involves managing a small team, share examples of how you've led teams in the past. Discuss your approach to mentoring junior engineers and how you prioritise tasks within a data engineering backlog.
✨Understand the Business Context
Familiarise yourself with the London Insurance Market and the wider Financial Services sector. Being able to relate your technical skills to business needs will show that you can bridge the gap between data engineering and business objectives.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, particularly in optimising data pipelines. Think of specific challenges you've faced in previous roles and how you overcame them, as this will illustrate your analytical skills.
