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T&T-EAID-Engineering-Manager | SQL | Delhi |
Deloitte —Delhi
- Azure
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- Computer Science
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T&T-EAID-Engineering-Manager | SQL | Delhi |

Deloitte -
Delhi

Apply Now

Job details

11 days ago

Qualifications

Azure
Management
Business intelligence
Computer Science
Kubernetes
Big data
DevOps
Master's degree
Databases
SQL
AWS
Database management
Bachelor's degree
Machine learning
PostgreSQL
Distributed systems
Redis
Scripting
APIs
Kafka
Python
High availability

Full job description

Job requisition ID :: 107618

Date: Jun 26, 2026

Location: Delhi CEC

Designation: Manager

Entity: Deloitte Touche Tohmatsu India LLP

T&T-EAID-Engineering-Manager | SQL | Delhi |

Job requisition ID : 107618
Location: Delhi CEC
Entity: Deloitte Touche Tohmatsu India LLP

The team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.

Your work profile

Deloitte India is looking for an experienced Manager – Data Platform & Database Architecture to lead the design, optimization, scalability, and governance of large-scale enterprise data platforms.
The ideal candidate will possess deep expertise in PostgreSQL architecture and administration, database performance engineering, data partitioning, data archival and lifecycle management, and distributed data systems such as Kafka and Redis.
This role requires a strong data engineering and database background, with experience designing platforms capable of handling high-volume transactional and analytical workloads.
Exposure to cloud platforms is desirable, but the primary focus will be on building scalable, resilient, and high-performing data ecosystems.

Database Architecture & Engineering

Define and implement enterprise-wide database architecture standards and best practices.
Design scalable PostgreSQL environments for high-volume, mission-critical applications.
Lead database capacity planning, performance optimization, and scalability initiatives.
Establish data governance, retention, archival, and lifecycle management frameworks.
Drive database modernization initiatives and technical debt reduction programs.
Review database designs and provide architecture guidance to development teams.

PostgreSQL Administration & Performance Tuning

Administer and optimize large PostgreSQL environments.
Perform advanced query optimization, indexing, and execution plan analysis.
Tune PostgreSQL parameters for high-throughput transactional systems.
Design and implement High Availability (HA) and Disaster Recovery (DR) architectures.
Manage replication, failover, backup, recovery, and database upgrades.
Troubleshoot complex performance bottlenecks across application and database layers.

Data Partitioning, Archival & Lifecycle Management

Design and implement partitioning strategies for multi-billion record datasets.
Develop archival frameworks to manage data growth while maintaining performance.
Define hot, warm, and cold data storage strategies.
Create automated retention and purge mechanisms aligned with business and regulatory requirements.
Optimize storage utilization and database maintenance processes.

Distributed Data Systems & Data Platforms

Design and manage distributed data architectures involving:
Apache Kafka
Redis
Event-driven and streaming data platforms
Caching architecture
Message-driven integration patterns
Define strategies for real-time data ingestion, processing, and distribution.
Establish standards for data consistency, resiliency, and fault tolerance across distributed systems.
Work with engineering teams to optimize data movement and process pipelines.

Pg Bouncer & Database Connectivity

Design and manage Pg Bouncer-based connection pooling architecture.
Optimize connection management for high-concurrency environments.
Troubleshoot application-to-database connectivity and performance issues.
Establish enterprise standards for database access and connection management.

Leadership & Stakeholder Management

Lead teams of DBAs, data engineers, and solution architects.
Conduct architecture reviews and provide technical oversight across projects.
Collaborate with business, product, and engineering stakeholders to define long-term data platform roadmaps.
Mentor team members and drive capability development within the organization.
Support pre-sales, solutioning, and client advisory engagements where required.

Key skills required:

Database Technologies

Expert-level experience with PostgreSQL administration and architecture.
Strong experience with:
Replication and High Availability
Backup and recovery strategies
Query optimization and performance tuning
Indexing and database design
Partitioning and archival solutions
Database monitoring and observability

Distributed Data Technologies

Strong hands-on experience with:
Apache Kafka
Redis
Event-driven architecture
Distributed caching frameworks
Messaging and streaming platforms

Data Architecture

Data modelling and database design.
Data retention and governance frameworks.
Large-scale transactional and analytical systems.
Data platform scalability and resilience design.
Enterprise integration patterns and API-driven architectures.

Cloud Exposure (Preferred)

Exposure to AWS, Azure, or GCP.
Understanding of managed PostgreSQL services and cloud database offerings.
Experience supporting cloud migration initiatives is desirable but not mandatory.

Qualifications

Bachelor’s or master’s degrees in computer science, Information Technology, Engineering, or related field.
Experience managing databases exceeding multiple terabytes in size.
Experience working in Utilities, Telecom, BFSI, Healthcare, or large-scale SaaS environments.
Exposure to Kubernetes, containerized deployments, and DevOps practices.
Experience with database automation and scripting using Python, Shell, or similar technologies.

Ideal Candidate Profile

The ideal candidate will have:

12–15+ years of experience in database engineering and data platform architecture.
Proven experience leading enterprise-scale data transformation initiatives.
Strong expertise in PostgreSQL performance engineering and distributed data systems.
Ability to design scalable architectures capable of handling billions of records and high-throughput transaction volumes.
Experience leading technical teams and engaging with senior business stakeholders.

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