Data Engineer - Manager

PwC; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Private medical cover

Flexible working

Volunteer days

Job summary

PwC ищет менеджера по Data Engineering для управления несколькими командами инженеров данных и разработки высококачественных решений для клиентов. В задачи входит руководство проектами по конвейерам данных, инфраструктуре аналитики и интеграции технологий для поддержки AI/BI.;

Кандидат должен иметь опыт ведения data-в проекта, владение Python и Spark, а также навыки разработки API и DevOps. Возможности роста в рамках Data & AI capability PwC.

Qualifications

• Опыт руководства командами инженеров данных в сложных средах.
• Глубокие знания объектно‑ориентированного Python, разработка и тестирование кода.
• Опыт работы с Apache Spark для обработки больших данных.
• Навыки разработки API на FastAPI или аналогах.
• Понимание BI и оптимизация трансформаций под AI/BI задачи.
• Сильное владение DevOps и репозиториями Git.

Responsibilities

• Руководить командами инженеров данных и развивать культуру высокой эффективности.
• Обеспечивать техническое направление при проектировании и поддержке конвейеров данных и аналитической инфраструктуры.
• Участвовать в проектировании, разработке и устранении сложных технических вопросов.
• Укреплять практики архитектуры данных, моделирование, оркестрацию и наблюдаемость.

Skills

Python

Data engineering

Data pipelines

Git / GitHub

Spark

FastAPI

Azure / AWS / GCP

Databricks

Azure Data Factory

APIs

Tools

GitHub Copilot

Cursor

Azure DevOps

Databricks Platform

Job description

Описание

Line of Service Internal Firm Services Industry/Sector Technology Specialism IFS - Information Technology (IT) Management Level Manager

Задачи

Leading and developing teams of data engineers, creating a collaborative, high-performing environment focused on building reliable and scalable data solutions. Providing technical direction for the design, build and support of data pipelines, data platforms and analytics infrastructure, ensuring alignment with organisational goals and industry best practices. Contributing hands‑on to solution design, development and troubleshooting, including code reviews and resolution of complex technical issues. Building data engineering capability by driving adoption of modern techniques, tools and patterns, supporting the professional growth of your teams and the wider Data & AI capability. Engaging stakeholders across business, technology partners and clients to understand requirements, set priorities and deliver impactful data solutions. Ensuring quality by overseeing the development, deployment and validation of data solutions, maintaining high standards of accuracy, reliability and performance. This role is for you if: Proven experience leading or managing data engineering teams or workstreams in complex environments. Strong object-oriented Python skills for developing, testing and packaging code, including experience with tools such as GitCliff, and familiarity with frameworks such as PyTorch and TensorFlow where relevant to data and AI workloads. Experience with Apache Spark for large-scale data processing. Effective use of coding tools such as Cursor, GitHub Copilot and similar to accelerate high-quality delivery. Experience developing APIs using FastAPI or similar technologies to expose data and analytics services. Strong understanding of business intelligence needs and optimising data transformations for AI and BI applications. Solid understanding of best practices in data engineering architecture, including data modelling, orchestration, testing and observability. Familiarity with SDLC methodologies such as SAFe, Agile and JadX and experience applying them to data engineering projects. Experience using repositories and DevOps tooling including GitHub and Azure DevOps. Hands‑on experience with major data engineering tools and platforms such as Databricks, Microsoft Fabric, Azure Data Factory and Palantir. Experience with at least one major cloud platform (Azure, AWS or GCP), ideally more than one, for data engineering workloads.

Требования

• Accepting Feedback
• Accepting Feedback
• Active Listening
• Agile Scalability
• Amazon Web Services (AWS)
• Analytical Thinking
• Apache Airflow
• Apache Hadoop
• Azure Data Factory
• Coaching and Feedback
• Communication
• Creativity
• Data Anonymization
• Data Architecture Development
• Database Administration
• Database Management System (DBMS)
• Database Optimization
• Database Security Best Practices
• Databricks Unified Data Analytics Platform
• Data Engineering
• Data Engineering Platforms
• Data Infrastructure
• Data Integration
• Data Lake
• Data Modeling {+ 32 more}
• Desired Languages (If blank, desired languages not specified) Not Specified

Available for Work Visa Sponsorship? Yes Government Clearance Required? No Job Posting End Date April 7, 2026

Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Degrees/Field of Study preferred: Certifications (if blank, certifications not specified)

We offer a range of benefits including empowered flexibility and a working week split between office, home and client site; private medical cover and 24/7 access to a qualified virtual GP; six volunteering days a year and much more.

We offer a range of benefits including empowered flexibility and a working week split between office, home and client site; private medical cover and 24/7 access to a qualified virtual GP; six volunteering days a year and much more.

Условия

You’ll be joining our Data & AI capability as a Manager in the Data Engineering team, leading one or more teams to design and deliver advanced data solutions that address complex challenges for PwC and its clients. Operating at the forefront of data engineering, you’ll support projects across various industries such as healthcare and financial services, shaping and scaling data platforms that underpin analytics, AI and machine learning. You’ll combine hands‑on technical delivery with team leadership, setting direction for robust, modern data engineering practices. You’ll work in a cross‑functional environment, collaborating across business and technology to deliver tangible value from data. We’re looking for a motivated self‑starter, comfortable with ambiguity and experienced in managing cross‑functional delivery, with 4+ years of data engineering experience, to join us in either our Manchester or Birmingham offices.