Engineering Manager - Azure, AWS, DBT- Manager

PwC Acceleration Center India

Bengaluru

On-site

INR 3,000,000 - 5,200,000

Full time

5 days ago
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Job summary

PwC Acceleration Center India seeks an Engineering Manager - Azure, AWS, DBT to lead data engineering and analytics initiatives. You will drive modernization, design scalable data pipelines, and mentor a multidisciplinary team in a fast-paced consulting environment.

You will oversee architecture, data quality, and security while partnering with Advisory, Assurance, Tax and Business Services teams to deliver client-focused solutions.

Qualifications

  • Bachelor's degree or higher in a related field required.
  • 10+ years of experience in data engineering with Azure/AWS.
  • Proficient in data management concepts and data modeling.
  • Strong team management and mentorship skills.
  • Experience with Hadoop and Spark is mandatory.

Responsibilities

  • Lead data engineering projects using Azure and AWS for data modernization.
  • Manage and optimize data pipelines with Airflow and Azure Data Factory.
  • Develop data architecture strategies for scalable integration.
  • Oversee data warehouses, ensuring quality and security.
  • Collaborate with cross-functional teams to enhance analytics capabilities.
  • Guide teams in database management with MySQL and PostgreSQL.
  • Promote Databricks and Snowflake for advanced data engineering.
  • Coach team members to grow technically and professionally.
  • Analyze complex data to identify performance enhancements.
  • Maintain stakeholder relationships aligning data strategy with business goals.

Skills

Azure
AWS
Data engineering
Team management
Data pipelines
Databricks
Airflow
Data modeling
Data architecture
RDBMS

Education

Bachelor's degree

Tools

Azure Data Factory
Airflow
Databricks
Snowflake
Hadoop
Spark
MySQL
PostgreSQL

Job description

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands‑on learning, cutting‑edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As an Engineering Manager - Azure, AWS, DBT, you will lead and manage teams within our Data and Analytics Engineering group, focusing on data engineering solutions that drive client success. Within our Cloud Engineering, Data & Analytics network, you will be at the forefront of data modernization efforts, leveraging cutting‑edge technologies to deliver innovative solutions. This role involves collaborating with multidisciplinary teams to design, develop, and implement data engineering projects that meet client needs and expectations.

As a Manager, you will play a pivotal role in mentoring and developing your team, fostering a culture of continuous improvement and innovation. You will be responsible for strategic planning and execution, confirming that projects are delivered on time and within scope. Your leadership will be instrumental in identifying opportunities for growth and improvement, while maintaining the integrity and authenticity of our services. In this role at PwC Acceleration Center India, you will guide your team to embrace technology and innovation, enhancing delivery and encouraging others to do the same.

Responsibilities
  • Leading data engineering projects utilizing Azure and AWS platforms to drive data modernization initiatives
  • Managing and optimizing data pipelines and workflows using Apache Airflow and Azure Data Factory
  • Developing and implementing data architecture strategies to support scalable and efficient data integration
  • Overseeing the design and maintenance of data warehouses, confirming data quality and security
  • Collaborating with cross-functional teams to enhance data infrastructure and analytics capabilities
  • Guiding teams in the application of database management systems, including MySQL and PostgreSQL
  • Promoting the use of innovative data engineering practices and tools such as Databricks and Snowflake
  • Coaching and mentoring team members to foster professional growth and technical proficiency
  • Analyzing complex data sets to identify opportunities for performance tuning and optimization
  • Building and maintaining relationships with stakeholders to align data strategies with business objectives
What You Must Have

10+ years of experience working in Azure ADLS, Data Bricks, Data Flows, HDInsight, Azure Analysis services

  • At least a Bachelor's degree
  • Oral and written proficiency in English required
  • Should be aware of Data Management concepts and Data Modelling
  • Should have team management experience.
  • Good knowledge of Big Data frameworks and related technologies - Experience in Hadoop and Spark is mandatory
  • Should have expertise in extracting data from different source systems like flat files, XML sources, JSON, Parquet files, Big data appliances, RDBMS, etc.
  • Good knowledge of Big Data frameworks and related technologies - Experience in Hadoop and Spark is mandatory
  • Should have clear understanding of DW lifecycle and contributed in preparing
  • Detail Level Design document
  • Unit Test plans

-Code review reports -

What Sets You Apart
  • Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics
  • Demonstrating proficiency in Amazon Web Services (AWS) and Microsoft Azure
  • Utilizing Apache Airflow and Databricks for data pipeline management
  • Excelling in data architecture development and optimization
  • Managing data warehouse troubleshooting and performance tuning
  • Leading teams in data modernization and transformation projects
  • Embracing change and fostering innovation in data engineering environments
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