IN_Senior Manager_Data Engineering Azure AWS GCP Oracle _OC-Data And Analytics AITH_Advisory_Bhubaneswar

PwC; Khordha; On-site; INR 400,000 - 750,000; Full time

Benefits offered by this job

Mentorship

Flexible work programmes

Inclusive benefits

Job summary

PwC is seeking a Senior Manager – Data Engineering to lead and evolve data infrastructure across cloud platforms (Azure, AWS, GCP, Informatica, Oracle Cloud). You will design, implement, and govern scalable data pipelines, collaborate with data scientists and business teams, and drive data security and governance across multi-cloud environments.

The role demands strong leadership, cloud architecture expertise, and hands-on delivery experience, with a focus on building robust data platforms and

Qualifications

• Bachelor's or Master’s degree in CS/Engineering/Data Science.
• 12 to 16 years of experience in data engineering or related fields.
• Experience designing and managing data workloads across cloud platforms.
• Strong leadership and Agile methodology experience.
• Ability to communicate technical concepts to stakeholders.

Responsibilities

• Lead and mentor data engineering teams to design, build, and maintain data platforms on cloud environments including Azure, AWS, 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 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.

Skills

Microsoft Azure

AWS

Google Cloud Platform

Oracle Cloud Infrastructure

ETL/ELT pipelines

Data Lakes

Data Warehouses

Spark

Airflow

Kubernetes

Python

SQL

Java/Scala

Education

Bachelor's or Master’s degree in CS/Engineering

MBA

Tools

Terraform

CloudFormation

Databricks

Docker

Jenkins

Job description

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.

Why PWC

At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our 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 for each other. Learn more

At PwC, 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.

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

Degrees/Field of Study required: Bachelor of Engineering, MBA (Master of Business Administration)

Degrees/Field of Study preferred: (none listed)

Certifications

(none listed)

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