Data Engineer – Manager

PwC

Data Engineer Manager leading teams to deliver advanced data solutions at PwC. Collaborating across sectors to shape AI and analytics platforms with hands-on technical delivery and leadership.

Posted 7/25/2026full-timeBirmingham • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading data engineering teams and developing scalable data solutions, with a strong focus on Python programming, data pipeline architecture, and cloud platforms. Proven ability to engage stakeholders and drive the adoption of modern data engineering practices.

Highest-signal resume keywords

Data Engineering Team LeadershipObject-Oriented Python DevelopmentApache Spark Data ProcessingAPI Development with FastAPICloud Platform Experience (Azure, AWS, GCP)

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Applicant Tracking System Keywords

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Hard Skills

PythonApache SparkData ModellingData OrchestrationAPI DevelopmentData TransformationDevOps ToolingData Engineering ArchitectureSDLC MethodologiesData Validation

Soft Skills

Stakeholder EngagementTeam DevelopmentProblem SolvingCollaborationCommunication

Tools & Technologies

GitHubAzure DevOpsDatabricksMicrosoft FabricAzure Data FactoryPalantirCursorGitCliffGitHub CopilotPyTorch

Industry Keywords

Data SolutionsData PipelinesAnalytics InfrastructureBusiness IntelligenceAI WorkloadsAgileSAFeJadXData Engineering Best PracticesData Observability

Tech Stack

Tools & technologies

ApacheAWSAzureCloudGoogle Cloud PlatformPythonPyTorchSDLCSparkTensorflow

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

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