data engineer for payments infrastructure

Barclays; Greater London; On-site; GBP 90,000 - 125,000; Full time

Job summary

Барclays ищет инженерa данных для построения и поддержки высоконадежных конвейеров данных в рамках платформы Databricks в лондонском офисе. Вы будете проектировать архитектуры данных, разворачивать пайплайны и сотрудничать с учёными данными для развёртывания моделей.

Требуется опыт работы с Python, PySpark, SQL, Git и CI/CD, знание управления доступом и безопасности. Ожидается участие в формировании стандартов разработки, а также менторство младших специалистов; офисная работа 3 дня в неделю.

Qualifications

• Опыт построения производственных Databricks платформ
• Разработка конвейеров данных с пакетной и потоковой обработкой
• Опыт работы с безопасностью данных, IAM и шифрованием
• Опыт работы в средах Python/PySpark/SQL

Responsibilities

• Строить и поддерживать архитектуры данных и пайплайны
• Проектировать хранилища данных и озера данных под требования
• Разрабатывать алгоритмы обработки данных для больших объемов
• Сотрудничать с Data Scientists для развёртывания моделей
• Определять инженерные стандарты, автоматизацию и контроль

Skills

Databricks

PySpark

Python

SQL

CI/CD

Security & IAM

Terraform

Tools

Git

GitHub Actions

Terraform

Databricks Unity Catalog

Job description

Описание:

Barclays’ payments acceptance business provides payment infrastructure for small businesses and domestic and international corporate clients. Barclays and Brookfield Asset Management are partnering to transform the business, broaden its services, and improve the client experience. The business will continue using the Barclaycard Payments (BPL) brand and serve as Barclays’ sole payments acceptance services provider for at least ten years.

Задачи:

• Build and maintain data architectures and pipelines for transferring and processing durable, complete, and consistent data
• Design and implement data warehouses and lakes that handle appropriate data volumes and velocity while meeting security requirements
• Develop processing and analysis algorithms suited to data complexity and volumes
• Collaborate with data scientists to build and deploy machine learning models
• Shape the data platform and deliver initial data products
• Build production-grade data pipelines using Databricks and AWS
• Establish engineering standards, reusable patterns, automation, and controls
• Work with domain teams to identify common requirements and turn successful approaches into repeatable golden paths
• Develop self-service capabilities, reusable tooling, and platform features that enable domain teams to build and operate trusted data products independently
• Contribute to strategy, drive requirements, and recommend change
• Plan resources, budgets, and policies; manage and maintain policies and processes; deliver continuous improvements; elevate policy and procedure breaches
• Guide technical direction as a subject matter expert and lead collaborative, multi-year assignments
• Guide, train, and coach less experienced specialists
• Advise stakeholders and senior management on functional and cross-functional impacts and alignment
• Assess and mitigate risks in support of control and governance
• Demonstrate accountability for managing risk and strengthening controls
• Collaborate across business-aligned support areas to stay informed about business activity and strategy
• Develop solutions through sophisticated analysis, research, and evaluation of complex alternatives
• Build and maintain stakeholder relationships and partnerships to achieve business objectives
• If managing a team, define roles and responsibilities, plan for future departmental needs and operations, counsel employees on performance, and contribute to pay decisions

Требования:

• Hands-on experience building production-grade Databricks platforms and reliable batch and streaming pipelines using Python, PySpark, and SQL
• Ability to create modular, maintainable, and reusable components
• Experience with automated pipeline testing, Git-based workflows, and CI/CD deployment
• Experience engineering systems for sensitive or regulated data, including identity and access control, encryption, secrets management, least privilege, monitoring, and production incident resolution
• Будет плюсом: Advanced Unity Catalog expertise; experience configuring lineage, permissions, metadata, and governance through Unity Catalog; Terraform, Databricks Asset Bundles, and GitHub Actions or equivalent policy-controlled delivery tooling; experience creating paved roads, golden paths, metadata-driven automation, or internal developer platforms

Условия:

• Expected office presence: 3 days per week
• The role is based in London.
• Offices are located at 1 Churchill Place and 7 Westferry Circus Barclays will invest approximately £400m in the new business, the majority of which will be incurred during the first three years
• Performance-linked incentives will support alignment between the partners
• The business is intended to become a standalone entity over time
• No minimum experience is specified