IN_Senior Manager_Data Engineering (Azure/AWS/GCP/Oracle)_OC-Data & Analytics AITH_Advisory_Bhubaneswar

Price Waterhouse Cooper LLP; Khordha; On-site; INR 6,000,000 - 9,000,000; Full time

Job summary

Price Waterhouse Cooper LLP is seeking a Senior Manager – Data Engineering to lead data engineering teams and deliver robust, scalable data infrastructure across Azure, AWS, GCP, Oracle Cloud, and on-prem migrations. The role emphasizes cloud-native architectures, governance, and cross-functional collaboration to support analytics, BI, and data science needs.

The ideal candidate will have 12–16 years of experience, strong leadership capabilities, and a track record of delivering large-scale data

Qualifications

• 12 to 16 years of experience in data engineering or related field.
• Strong cloud analytics and data platform implementation experience.
• Experience with multi-cloud environments and data governance is preferred.

Responsibilities

• Lead and mentor data engineering teams to design, build, and maintain scalable data platforms on cloud environments.
• Own the end-to-end lifecycle of data engineering solutions: ingestion, transformation, storage, and delivery.
• Collaborate with architects, data scientists, analysts, and IT to translate requirements into scalable data solutions.
• Drive adoption of cloud-native architectures like data lakes, warehouses, and lakehouses.
• Define technical standards, architecture guidelines, and procedures for reliability and security.
• Oversee cloud migration projects from on-prem to cloud platforms.
• Manage vendor relationships and evaluate new cloud tools.
• Enforce data governance, quality, and regulatory compliance.
• Monitor pipeline performance and perform tuning and capacity planning.
• Lead Agile delivery with sprint planning and stakeholder communication.

Skills

Data engineering

Cloud data platforms

Python/SQL/Scala/Java

ETL/ELT pipelines

Spark/Kafka

Airflow orchestration

Data governance & security

Leadership & Agile

Education

Bachelor’s or Master’s degree in Computer Science/Engineering/Data Science

Tools

Docker

Kubernetes

Terraform

Cloud migration tooling

Job description

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Manager

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

*WhyPWC

AtPwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes forour clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences foreach other. Learn more

about us

AtPwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations.

Job Description & Summary:

We are looking for a Senior Manager – Data Engineering to lead and manage data engineering teams responsible for building robust, scalable, and secure data infrastructure leveraging cloud technologies across Azure, AWS, Google Cloud Platform (GCP), Informatica and Oracle Cloud. The ideal candidate will combine strong technical expertise with leadership skills to drive data platform initiatives, optimize data pipelines, and collaborate cross-functionally to support analytics, BI, and data science needs.

Responsibilities:

• Lead and mentor data engineering teams to design, build, and maintain high-performance, scalable data platforms on cloud environments including Azure, AWS, Google Cloud Platform (GCP), Informatica and Oracle Cloud
• Own the end-to-end lifecycle of data engineering solutions: data ingestion, transformation, storage, and delivery.
• Collaborate with enterprise architects, data scientists, business analysts, and IT teams to translate business requirements into scalable data engineering solutions.
• Drive adoption of best practices in cloud-native data architectures such as data lakes, data warehouses, and lakehouses.
• Define technical standards, architecture guidelines, and operational procedures to ensure reliability, performance, and data security.
• Oversee cloud migration projects and upgrade efforts for existing on-premises data platforms to cloud.
• Manage vendor relationships and evaluate emerging cloud services and tools relevant to data engineering.
• Implement and enforce data governance, data quality, and compliance measures.
• Monitor data pipeline performance and implement tuning, troubleshooting, and capacity planning.
• Lead Agile delivery processes with efficient sprint planning, backlog grooming, and stakeholder communication.
• Provide technical leadership in evaluating and incorporating automation and orchestration tools (e.g., Apache Airflow, Jenkins).
• Report progress, risks, and KPIs to senior leadership and stakeholders.

Mandatory skill sets:

Cloud Platforms Expertise:

• Demonstrated hands-on experience designing and managing data workloads across one or more cloud platforms:
• Microsoft Azure(Data Factory, Synapse Analytics, Databricks)
• AWS(Glue, Redshift, Athena, EMR)
• Google Cloud Platform(BigQuery, Dataflow, Dataproc)
• Oracle Cloud Infrastructure(Autonomous Database, Data Integration, Object Storage)
• Experience in cloud migration from traditional on-prem data systems to cloud-native data platforms.

Data Engineering Fundamentals:

• Deep understanding of ETL/ELT pipelines, data ingestion, batch and streaming data processing.
• Expertise in data storage solutions: Data Lakes, Data Warehouses, Lakehouses, and relational/non-relational databases.
• Skilled in programming/scripting languages (Python, SQL, Scala, or Java).
• Experience with big data frameworks and tools such as Apache Spark, Kafka, and Apache Airflow.
• Familiar with containerization (Docker) and orchestration (Kubernetes) in data workflows.
• Knowledge of infrastructure automation tools (Terraform, CloudFormation, ARM templates).
• Strong grasp of data governance, security frameworks (IAM, encryption), and regulatory compliance.

Leadership & Management:

• Proven experience leading and scaling technical teams in data engineering or related fields.
• Strong project management and Agile methodology experience.
• Ability to effectively communicate technical concepts to business and technical stakeholders.
• Skilled in resource planning, budgeting, and vendor management.

Preferred skill sets:

• Relevant cloud certifications such as:
• Microsoft Certified: Azure Data Engineer Associate
• AWS Certified Big Data – Specialty or Data Analytics – Specialty
• Google Professional Data Engineer
• Oracle Cloud Infrastructure Data Management Specialist
• Experience working in multi-cloud or hybrid cloud environments.
• Knowledge of orchestration of ML pipelines and basic AI/ML concepts is a plus.

Years of experience required:

12 to 16 years

Education qualification:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related disciplines.

Education

(if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor of Engineering, MBA (Master of Business Administration)

Degrees/Field of Study preferred:

Certifications

(if blank, certifications not specified)

Required Skills

Data Engineering

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, AI Fluency, AI-Human Collaboration, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture, 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 {+ 40 more}

Desired Languages

(If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date

July 7, 2026