IN-Manager Delivery Manager Data & Analytics Advisory Mumbai

Mumbai Shivaji Park

Full Time Mid-level / Intermediate USD 53K - 99K *

PwC

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Posted 22 hours ago

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

Job Description & Summary

A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.

Creating business intelligence from data requires an understanding of the business, the data, and the technology used to store and analyse that data. Using our Rapid Business Intelligence Solutions, data visualisation and integrated reporting dashboards, we can deliver agile, highly interactive reporting and analytics that help our clients to more effectively run their business and understand what business questions can be answered and how to unlock the answers.

*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 about us.

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. "

Responsibilities: Key Responsibilities:
1. Project Management:
o Lead the end-to-end delivery of data projects,
including Data Warehouse, Data Lake, and
Lakehouse solutions.
o Develop detailed project plans, allocate
resources, and monitor project progress to
ensure timely and within-budget delivery.
o Identify and mitigate risks, ensuring successful
project outcomes.
2. Technical Leadership:
o Provide technical oversight and guidance on
best practices in data engineering, cloud
architecture, and data management.
o Ensure solutions are scalable, robust, and align
with industry standards and client
requirements.
o Oversee the design, development, and
implementation of data solutions using Azure
or AWS and Databricks.
3. Client Engagement:
o Engage with clients to understand their
business needs and translate them into
technical requirements.
o Build and maintain strong relationships with
key client stakeholders.
o Present complex technical concepts and
solutions in a clear and concise manner to non-
technical stakeholders.

4. Team Leadership:
o Lead and mentor a team of data engineers,
fostering a collaborative and high-performance
culture.
o Provide guidance and support to team
members in their professional development
and project delivery.
o Ensure the team is equipped with the necessary
tools and resources to succeed.

5. Solution Development:
o Develop and implement data pipelines, ETL
processes, and data integration solutions using
Azure Data Factory, AWS Glue, Databricks, and
other relevant tools.
o Optimize data storage and retrieval
performance, ensuring data quality and
integrity.
o Leverage advanced analytics and machine
learning capabilities within Databricks to drive
business insights.

6. Continuous Improvement:
o Stay up-to-date with the latest advancements in
Azure, AWS, Databricks, and data engineering
technologies.
o Implement best practices and continuous
improvement initiatives to enhance the
efficiency and effectiveness of data engineering
processes.
o Foster a culture of innovation and
experimentation within the team.

Skills & Competencies:
 Strong problem-solving and analytical skills.
 Deep technical expertise in Azure, Google or AWS and
Databricks.
 Exceptional project management and organizational
abilities.
 High level of emotional intelligence and client empathy.
 Proficiency in:
o Concepts of Data warehousing and Data Lake
(e.g., SCD1, SCD2, Dimensional Modeling, KPIs
and Measures, Data Catalog, Star and Snowflake
schema, Delta Table and Delta Live Tables)
o Data warehousing solutions (e.g., Azure
Synapse, Azure SQL, ADLS Gen2, BLOB Storage
for Azure and Redshift, S3, AWS Glue AWS
Lambda for AWS, Google data management
technologies )
o Data Lake solutions (e.g., MS Fabric, Purview,
AWS Lakehouse, BigQuery and BigTable )
o Lakehouse solutions (e.g., Databricks, Unity
Catalog, Python and Pyspark)
o Data visualization tools (e.g., Power BI,
Tableau) is a plus