Senior Data Engineer

Senior Data Engineer

London Full-Time 43200 - 72000 Β£ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop and maintain complex data systems for banking operations and reporting.
  • Company: Arbuthnot Latham has been a trusted name in banking since 1833, blending tradition with modern tech.
  • Benefits: Enjoy agile working, competitive salary, health cover, and generous leave policies.
  • Why this job: Join a collaborative team, mentor others, and innovate in a dynamic banking environment.
  • Qualifications: Experience with Azure Data Stack, Python, and mentoring junior developers is essential.
  • Other info: We value diversity and offer reasonable adjustments for applicants with disabilities.

The predicted salary is between 43200 - 72000 Β£ per year.

Arbuthnot Latham has been associated with banking since 1833. We combine private and commercial banking, wealth planning and investment management. We believe in traditional relationship and service-led banking powered by modern technology.

Job purpose: Develop and maintain complex data systems that support the Bank's operations and reporting needs, ensuring they meet all essential data requirements, following strong engineering and automation best practices and collaborating with the Technical Lead for Data Engineering to develop innovative solutions that address business needs. As a Senior Data Engineer, this person will also play a key role in the development of less experienced members of the team day to day. To place the interests of customers at the centre of all activities, act in a way that is consistent with achieving good outcomes for consumers; and to comply with the FCA and PRA's Conduct Rules.

Key Responsibilities:

  • The development of data ingest, transformation, analytics, and data publishing pipelines, facilitating complex data transformations to meet business requirements, ensuring optimal performance and efficiency of the data platform.
  • Support for the live platform day to day, resolving issues and meeting business requests as they arise within the team’s SLAs.
  • The enablement and promotion of Data Engineering best practices and DevOps standards, ensuring good code quality and continuous compliance with all relevant standards.
  • Providing mentorship to junior engineers, helping them enhance their skills and knowledge.
  • Promoting a collaborative environment to deliver and integrate end to end data solutions.
  • Identifying and addressing technical debt efficiently, continuously improving data processes and workflows for enhanced efficiency.
  • Working collaboratively with business stakeholders and operational teams to resolve issues and minimise the defect backlog.
  • Supporting estimation processes to aid in planning and portfolio management.
  • Keeping abreast of industry technical best practices and new trends, ensuring innovative development of systems to meet organisational immediate and future needs.

Risk: Responsible for managing risks inherent to the role by diligently observing internal policies and procedures.

Key Interfaces:

  • Technical Lead for Data Engineering
  • Business System Owner
  • Head of Data Engineering
  • Application Specialists and Application Support
  • Information Security Manager
  • Data Privacy Manager

Person Specification

Knowledge/Experience/Skills:

  • Strong communicator with both technical and non-technical communities
  • Experience of mentoring less-experienced developers
  • Significant hands-on experience with the Azure Data Stack, critically ADF and Synapse (experience with Microsoft Fabric is a plus)
  • Highly developed python and data pipeline development knowledge, must include substantial PySpark experience
  • Demonstrable DevOps and DataOps experience with an understanding of best practices for engineering, test and ongoing service delivery
  • An understanding of Infrastructure as Code concepts (Demonstrable Terraform experience a plus)
  • Demonstrable experience of Data Pipeline testing, including automated testing, data validation and code assurance
  • Demonstrable experience of working within Agile Delivery projects
  • An understanding of data formats for ingest, transformation and analytics, data security, access control and authorisation, GDPR, data privacy, and information security
  • Awareness of data models in a Medalion Architecture
  • Experience building Semantic, Metric or Analytic models
  • Experience of building Machine Learning models
  • Any experience in MLOps or operationalising Machine Learning
  • Knowledge of Data Quality Frameworks in Python

Qualifications:

  • Industry focused degree or equivalent working experience
  • Azure certifications are desirable

About Us

Life, Work and Benefits:

  • Arbuthnot Latham is committed to equal-opportunities for all staff and candidates. We embrace inclusion & diversity and understand why they are critical for the success of our business and people.
  • Agile working - (3 Days in London Office per week)
  • Competitive salary, pension & holiday allowance
  • BUPA Health cover
  • 4x Life Assurance
  • Discretionary bonus
  • Market leading maternity/paternity and menopause policies

Data Privacy and Reasonable adjustments:

We take keeping your data security seriously. For more detail on how we may keep your data please refer to our Privacy Notice. Reasonable adjustments: Please let us know of any adjustments or arrangements that you may need to help you apply to this role or that will help you during the recruitment process. If you wish to discuss any particular requirements or concerns you have because of a disability or medical condition please contact us at recruitment@arbuthnot.co.uk. Information you provide about any disability or medical condition will remain confidential unless it is necessary to disclose it to other members of staff or outside agencies to ensure the health and safety of yourself and others, or to implement the adjustments you require. In these circumstances we will first discuss with you how and to whom the information may be disclosed.

Senior Data Engineer employer: Arbuthnot Latham

Arbuthnot Latham is an exceptional employer that values innovation and collaboration, offering a dynamic work environment in the heart of London. With a strong commitment to employee development, competitive benefits including BUPA health cover and generous parental leave policies, and a culture that embraces diversity and inclusion, we empower our team members to thrive both personally and professionally. Join us as a Senior Data Engineer and play a pivotal role in shaping the future of banking through cutting-edge technology and mentorship opportunities.
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Contact Detail:

Arbuthnot Latham Recruiting Team

atrecruitment@arbuthnot.co.uk

StudySmarter Expert Advice 🀫

We think this is how you could land Senior Data Engineer

✨Tip Number 1

Familiarise yourself with the Azure Data Stack, especially ADF and Synapse. Since these are critical for the role, showcasing your hands-on experience with them during discussions can set you apart.

✨Tip Number 2

Highlight your mentoring experience. As a Senior Data Engineer, you'll be expected to guide junior engineers, so sharing specific examples of how you've helped others grow can demonstrate your leadership skills.

✨Tip Number 3

Stay updated on industry best practices in DevOps and DataOps. Being able to discuss recent trends or innovations in these areas will show that you're proactive and committed to continuous improvement.

✨Tip Number 4

Prepare to discuss your experience with Agile Delivery projects. Understanding how to work within Agile frameworks is essential, so be ready to share how you've successfully contributed to such environments.

We think you need these skills to ace Senior Data Engineer

Strong communication skills
Mentoring and coaching abilities
Hands-on experience with Azure Data Stack (ADF and Synapse)
Proficiency in Python and PySpark for data pipeline development
DevOps and DataOps best practices
Infrastructure as Code (Terraform experience is a plus)
Data Pipeline testing and validation
Agile project delivery experience
Understanding of data formats, security, and GDPR compliance
Familiarity with Medalion Architecture
Experience in building Semantic, Metric or Analytic models
Knowledge of Machine Learning model development and MLOps
Understanding of Data Quality Frameworks in Python
Problem-solving and judgement skills
Creativity and innovation in solution development

Some tips for your application 🫑

Tailor Your CV: Make sure your CV highlights relevant experience with the Azure Data Stack, Python, and data pipeline development. Use specific examples that demonstrate your hands-on experience and any mentoring roles you've taken on.

Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and how your skills align with Arbuthnot Latham's mission. Mention your understanding of DevOps practices and your ability to work collaboratively with both technical and non-technical teams.

Showcase Your Technical Skills: Include a section in your application that lists your technical skills, particularly those mentioned in the job description such as PySpark, Terraform, and experience with Agile Delivery projects. This will help you stand out to the hiring team.

Highlight Mentorship Experience: Since the role involves mentoring junior engineers, be sure to include any relevant experience you have in this area. Discuss how you've helped others develop their skills and how you promote a collaborative environment.

How to prepare for a job interview at Arbuthnot Latham

✨Showcase Your Technical Skills

Be prepared to discuss your hands-on experience with the Azure Data Stack, particularly ADF and Synapse. Highlight specific projects where you've implemented data pipelines using PySpark, as this will demonstrate your technical proficiency.

✨Emphasise Mentorship Experience

Since the role involves mentoring junior engineers, share examples of how you've supported less-experienced developers in the past. Discuss any specific strategies you used to help them grow their skills and knowledge.

✨Demonstrate Problem-Solving Abilities

Prepare to discuss challenges you've faced in previous roles, particularly related to data engineering. Explain how you identified issues, implemented solutions, and improved processes, showcasing your problem-solving skills.

✨Familiarise Yourself with Industry Trends

Stay updated on the latest trends in data engineering and DevOps practices. Be ready to discuss how you can apply innovative solutions to meet the bank's immediate and future needs, showing your commitment to continuous improvement.

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