Data Engineering Manager

EY - GDS Consulting - AI And DATA - Data Engineer- Manager

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. 

 

 

 

 

Location: Pan India

The Opportunity

EY GDS Data & Analytics team helps clients solve complex business challenges using modern data platforms and cloud technologies. As a Data Technical Architect (Manager), you will design and architect scalable data solutions, enabling enterprise data transformation across industries.

Key Responsibilities

• Architect and design end-to-end data pipelines (ingestion, transformation, serving layers)
• Define data architecture patterns including batch, streaming, and lakehouse models
• Design scalable, secure, and high-performance cloud data platforms
• Build and implement ETL/ELT pipelines using Informatica / DataStage / SnapLogic
• Develop and optimize data pipelines on modern data platforms
• Design and maintain enterprise data models using strong data warehousing principles
• Work on distributed data processing frameworks (Spark, PySpark)
• Develop solutions using SQL and Python for large-scale data processing
• Architect solutions across Azure / AWS / GCP environments
• Design and manage job scheduling and orchestration workflows using Control-M and Autosys
• Ensure pipeline reliability with dependency management, monitoring, and SLA adherence
• Collaborate with business and technology stakeholders to gather requirements and define solutions
• Lead architecture discussions, provide technical direction, and ensure delivery excellence
• Drive end-to-end lifecycle: design → development → testing → deployment
• Mentor and guide teams, ensuring best practices in data engineering and architecture
• Support POCs, solutioning, and proposal development for client engagements

 

 

 

 

Skills & Qualifications

• Mandatory:
• Strong experience in ETL tools: Informatica / DataStage / SnapLogic
• Strong understanding of data warehousing concepts and data modeling
• Strong programming expertise in SQL and Python
• Experience with Control-M / Autosys scheduling tools
• Preferred:
• Experience in Databricks
• Experience in Snowflake
• Exposure to cloud platforms (Azure / AWS / GCP)
• Experience in distributed data systems (Spark, etc.)

Experience

• 8–12+ years of experience in Data Engineering / Architecture
• Proven experience in designing and delivering enterprise-grade data solutions

Soft Skills

• Strong communication and stakeholder management skills
• Ability to lead teams and drive delivery across global engagements
• Strong problem-solving and ownership mindset

Preferred

• Experience in Financial Services / WAM domain
• Exposure to real-time data processing (Kafka, streaming)
• Relevant cloud / Databricks certifications

 

 

EY | Building a better working world 

 
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.  

 
Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.  

 
Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.  

Experience Level

Mid Level