Job Description

At EY, we're all in to shape your future with confidence.


We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.


Join EY and help to build a better working world.

EY GDS

-

Data and Analytics (D&A) - Manager - Azure Data Architect

As part of our EY-GDS D&A (Data and Analytics) team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance.

The opportunity

We're looking for Managers (Big Data Architects) with strong technology and data understanding having proven delivery capability. This is a fantastic opportunity to be part of a leading firm as well as a part of a growing Data and Analytics team.

Your key responsibilities

Architecture & Solutioning

+ Design and propose

Azure-based data and AI solutions

that align with customer objectives and solve business challenges.
+ Architect and implement

data platforms

that support

real-time, batch, and hybrid analytics

.
+ Recommend design alternatives for

data ingestion

,

processing

, and

provisioning layers

.
+ Define and develop

client-specific best practices

around data management in cloud environments.
+ Translate business problems into

data models

,

analytics pipelines

, and

BI/ML solutions

.
+ Collaborate with cross-functional teams to ensure

data security

,

scalability

, and

performance

.

Data Engineering & Development

+ Develop standardized practices for delivering new products and capabilities using

Big Data & cloud technologies

.
+ Design and develop

data ingestion programs

for large datasets in

batch mode

using ADB, ADF, Synapse, PySpark, and Python.
+ Build

real-time ingestion pipelines

using Apache Kafka, Spark Streaming, and related technologies.
+ Lead the development of

data Lakehouse architectures

,

streaming pipelines

, and

data integration frameworks

.

Governance, Quality & Patterns

+ Define and implement

data governance

,

lineage

, and

quality frameworks

.
+ Guide teams on various modern

data design patterns

, e.g.:
- ETL/ELT
- Lambda/Kappa Architecture
- Data Vault & Dimensional Modelling
- Streaming Data Pipelines
- CQRS
- Change Data Capture (CDC)
- Schema Evolution
- Immutable Data
- Polyglot Persistence

Leadership & Client Engagement

+ Interact with senior client technology leaders to understand business goals and propose solutions.
+ Lead

technical delivery

, including

effort estimation

,

solution design

, and

team management

.
+ Develop and present

PoCs

,

demos

, and

technical proposals

to stakeholders and clients.
+ Build and mentor

technical teams

and contribute to

capability development

.

Skills and Attributes for Success

Strong understanding of

cloud ecosystems

(Azure, AWS) and

distributed computing paradigms

. Hands-on experience with: +

Azure Data Services

: Synapse, ADF, ADB, Azure SQL, Data Lake, Microsoft Fabric
+

Programming

: Python, PySpark, SQL
+

Streaming

: Kafka, Event Hubs, Spark Streaming
+

BI Tools

: Power BI, Tableau
Comprehensive applied knowledge of: +

Data modelling

(dimensional, vault)
+

Data governance

,

metadata management

, and

data observability

+

Performance tuning

Strong

stakeholder management

and ability to bridge

business and technical teams

. Exposure to

AI/ML platforms

: Azure Machine Learning, Cognitive Services, Azure OpenAI.

To Qualify for the Role, You Must Have

Minimum

10 years of industry experience

, with

7+ years in data architecture and analytics

. Proven experience in

enterprise-grade solution implementations

. Strong understanding and hands-on experience in

data strategy

,

cloud-native architectures

, and

analytics modernization

. Experience in

responding to RFPs/RFIs

, creating

technical documentation

, and leading

solution design workshops

.

Ideally, You'll Also Have

Project and client management skills. Experience in

solutioning and pre-sales

engagements. Exposure to

data mesh principles

and

domain-oriented data product design

. Familiarity with

data fabric architectures

and

multi-cloud data strategies

. Familiarity with real-time analytics Experience with

feature stores

and

ML model operationalization

.

What we look for

People with technical experience and enthusiasm to learn new things in this fast-moving environment

What working at EY offers

At EY, we're dedicated to helping our clients, from start-ups to Fortune 500 companies -- and the work we do with them is as varied as they are.


You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer:



Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that's right for you

EY | Building a better working world

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.


Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.


EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.