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PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

Data Engineer Senior Manager

Data EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • A bachelor's degree or equivalent experience is required.
  • 13 to 18 years of relevant experience in data engineering or related technology roles is required.
  • Deep expertise in application architecture, data engineering, solution design, and technical leadership.
  • Proven experience architecting and delivering enterprise-grade applications, data platforms, integrations, and analytics solutions.
  • Strong hands-on experience with modern cloud data platforms such as Databricks, Microsoft Fabric, Snowflake, Sigma, or similar enterprise data platforms.
  • Expertise in data lakes, lakehouse architecture, data warehousing, data modeling, and distributed data processing frameworks.
  • Advanced proficiency in Python, SQL, Spark, API management, enterprise application integration, and modern software engineering practices.
  • Demonstrated expertise in CI/CD, DevOps, automated testing, deployment automation, and engineering governance.
  • Experience designing and implementing generative AI, retrieval-augmented generation (RAG), semantic search, vector database architectures, and AI-powered enterprise solutions.
  • Hands-on experience with modern AI orchestration and agentic frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or similar technologies.
  • Ability to navigate highly complex and ambiguous technical challenges using analytical thinking, systems thinking, and problem-solving.
  • Ability to lead technical discussions, influence architecture and design decisions, and drive technical excellence across multiple initiatives.
  • Strong client engagement and relationship management skills, including translating complex technical concepts into business outcomes.
  • Ability to innovate through rapid experimentation, creativity, and adoption of emerging technologies.
  • Ownership and accountability for architecture quality, solution design, technical delivery, and business outcomes.
  • Strong communication skills to convey technical and business messages across engineering, leadership, and client stakeholders.

Responsibilities

  • Lead the design, development, and implementation of innovative data and software solutions that drive digital transformation and business value.
  • Serve as the technical owner and solution lead for complex engineering initiatives, providing direction across architecture, design, development, testing, and deployment.
  • Design scalable, resilient, and maintainable application, data, and integration architectures aligned with business requirements and technology standards.
  • Lead enterprise-scale data engineering solutions on modern cloud data platforms and lakehouse architectures, such as Databricks, Microsoft Fabric, Snowflake, Sigma, or similar enterprise data platforms.
  • Design and implement scalable data pipelines, data products, APIs, integrations, and distributed data processing solutions using Python, SQL, Spark, and modern cloud technologies.
  • Apply data modeling techniques and architectural patterns, including data lake, lakehouse, Delta Lake, and data warehouse solutions, to support analytics and AI-driven platforms.
  • Collaborate with stakeholders to translate business and functional requirements into technical specifications, solution designs, and implementation roadmaps.
  • Drive technical decision-making across architecture, engineering, integration, performance optimization, and operational readiness.
  • Conduct architecture reviews, solution reviews, and code reviews to ensure adherence to engineering standards, security requirements, and software quality best practices.
  • Champion modern engineering practices, including CI/CD, DevOps, infrastructure as code (IaC), automated testing, observability, and deployment automation.
  • Design and implement AI-enabled solutions using generative AI, retrieval-augmented generation (RAG), semantic search, vector databases, and agentic AI frameworks.
  • Apply analytical and systems thinking to troubleshoot complex technical challenges, identify dependencies, and drive root-cause resolution.
  • Build and maintain strong client and stakeholder relationships, validate delivery outcomes, and incorporate feedback to continuously improve solutions.
  • Promote innovation through rapid experimentation, proofs of concept, reusable accelerators, and adoption of emerging technologies.
  • Coach and mentor engineers and technical leads through architecture guidance, design reviews, engineering practices, and technical problem-solving.
  • Own end-to-end technical delivery and solution outcomes, ensuring alignment with business objectives, quality standards, scalability requirements, and client expectations.

About the Company

PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

PwC provides assurance (audit), tax, legal services, consulting and deals advisory to organisations worldwide. It uses multidisciplinary teams across accounting, advisory, technology and industry, delivered through a global network of locally established firms that collaborate with technology partners to offer AI, cloud, managed services and digital trust. PwC differentiates itself with an integrated, global-local service model and technology-enabled offerings that address complex client needs across risk, transformation, reporting and sustainability. Its goal is to help clients improve governance, efficiency and value by supporting reporting accuracy, business transformation, risk management and sustainable practices.

Company size
10,001+
Company stage
Early VC
Total funding
$3.3M
Headquarters
London, United Kingdom
Founded
1989

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