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- Tasks: Lead data engineering pipelines and manage a team to optimise our Lakehouse platform.
- Company: Join BMS Group, a dynamic player in the insurance and financial services sector.
- Benefits: Enjoy competitive pay, opportunities for remote work, and a supportive team culture.
- Why this job: Be part of an innovative team shaping the future of data engineering in a collaborative environment.
- Qualifications: Experience as a lead Data Engineer with skills in SQL, Python, and Azure Databricks required.
- Other info: This is a 12-month fixed-term contract based in London.
The predicted salary is between 60000 - 84000 £ per year.
BMS Group City Of London, England, United Kingdom
BMS Group City Of London, England, United Kingdom
Reports to: Head of Data Platforms
Location: London
About 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 standards
- Understanding 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 team
Desired skills and experience:
- Experience in the London Insurance Market, or the wider Financial Services sector
- Experience 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
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Seniority level
Mid-Senior level
Employment type
-
Employment type
Contract
Job function
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Job function
Information Technology
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Industries
Insurance, Financial Services, and Information Services
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Senior Data Engineer - 12 Month FTC employer: BMS Group
Contact Detail:
BMS Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer - 12 Month FTC
✨Tip Number 1
Familiarise yourself with Azure Databricks and the medallion architecture framework. Being able to discuss your experience with these technologies in detail will show that you're well-prepared for the role.
✨Tip Number 2
Highlight your leadership skills by preparing examples of how you've successfully managed a team of engineers. This will demonstrate your capability to lead and develop others, which is crucial for this position.
✨Tip Number 3
Stay updated on the latest trends in data engineering and the financial services sector. Being knowledgeable about current developments will help you engage in meaningful conversations during interviews.
✨Tip Number 4
Prepare to discuss specific projects where you've optimised data pipelines. Sharing concrete examples of your problem-solving skills will illustrate your ability to enhance efficiency within the team.
We think you need these skills to ace Senior Data Engineer - 12 Month FTC
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with Azure and the technologies mentioned in the job description, such as SQL, Python, and PySpark. Use specific examples to demonstrate your skills.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your previous experiences align with the responsibilities outlined in the job description, especially your leadership experience and familiarity with data pipelines.
Showcase Your Technical Skills: Include a section in your application that specifically lists your technical skills and tools you are proficient in, such as Azure Databricks and data modelling techniques. This will help the hiring team quickly see your qualifications.
Highlight Team Leadership Experience: Since the role involves managing a small team, be sure to highlight any previous leadership roles or experiences where you successfully guided a team. Discuss how you contributed to their development and the outcomes of your collaboration.
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. Bring examples of data engineering pipelines you've built, especially those deployed within Azure Databricks, as this will demonstrate your hands-on expertise.
✨Understand the Lakehouse Architecture
Familiarise yourself with the Lakehouse platform and its benefits. Be ready to explain how you would manage and optimise data engineering pipelines within this architecture, as it’s a key focus for the role.
✨Demonstrate Leadership Experience
Since you'll be leading a small team, share specific examples of how you've managed and developed engineers in the past. Highlight your approach to mentoring junior team members and fostering a collaborative environment.
✨Prepare for Agile Methodologies
Brush up on your knowledge of Agile methodologies, as well as Waterfall approaches. Be ready to discuss how you've successfully worked within these frameworks and how you adapt your strategies based on project requirements.
