Vice President - Data Architecture VP, Citi

Citi

Location:
India, Chennai ▼
Pune

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

We are seeking a Senior Data Engineer / Data Platform Architect to play a critical role in the delivery of our enterprise-wide Data Mesh and Hybrid Cloud architecture. This role combines hands-on engineering with architectural ownership across core platform components—including data pipelines, storage layers, metadata systems, and federated access patterns. The ideal candidate brings deep technical expertise, an architect’s mindset, and a proactive approach to building resilient, scalable, and cloud-native data platforms. You will work closely with the Data Mesh and Cloud Architect Lead to design, implement, and operationalize enterprise-grade data products and services across Controls Technology and the broader Functions Technology organization.

Job Responsibility:

Co-architect modular, reusable, and secure data platform components supporting Data Mesh principles
Design optimal data storage, processing, and retrieval strategies across hybrid cloud environments, with a focus on Apache Iceberg-based architectures
Integrate federated querying frameworks using Starburst and Stargate, ensuring high-performance access across data sources
Build and optimize complex batch and streaming pipelines for diverse data domains, with an emphasis on performance, fault-tolerance, and scalability
Enable schema evolution and transactional consistency in Iceberg tables, leveraging catalog services and metadata stores (e.g., Hive MetaStore)
Drive the adoption and implementation of Apache Iceberg, Iceberg Catalogs, Hive MetaStore, and Starburst to unify analytics across cloud and on-prem data assets
Operationalize data product templates, ingestion frameworks, and reusable patterns for use across multiple data domains
Architect and deploy data ingestion and processing components that span AWS cloud (S3, Lambda, Glue, Redshift, Athena) and on-prem environments
Implement data movement, governance, and monitoring frameworks that operate transparently across hybrid infrastructure
Embed data quality, lineage, and metadata capture into the platform by default, ensuring compliance and traceability
Enforce role-based access controls, encryption standards, and audit mechanisms aligned with corporate policies
Guide junior engineers and developers through technical reviews, architecture guidance, and solution design
Establish coding standards, testing patterns, CI/CD pipelines, and promote a culture of engineering excellence

Requirements:

Expert in Python, SQL, and scripting for automation and data engineering
Familiarity with Scala or Java
Strong experience with Apache Spark, Kafka, Flink, or other distributed data processing engines
Advanced knowledge of Apache Iceberg, including partitioning strategies, schema evolution, compaction, and ACID support
Hands-on with AWS cloud services—S3, Glue, Lambda, Redshift, Athena, and EMR
Experience architecting solutions across hybrid environments, integrating cloud-native and legacy systems
Proficient with Hive MetaStore, Iceberg Catalogs, and metadata management
Strong implementation experience with Starburst and Stargate for federated SQL access across disparate systems
Working knowledge of Terraform, CloudFormation, Docker, GitHub Actions, or similar CI/CD and IaC tools
Familiarity with data lineage, cataloging, RBAC, encryption, and compliance standards (GDPR, CCPA, etc.)
Architectural Thinking – Ability to break down complex data platform needs into modular, scalable components
Leadership & Mentorship – Demonstrated experience in guiding junior team members, setting technical direction, and reviewing solutions
Business Orientation – Understands data’s role in business processes and can balance technical rigor with practical implementation
Collaboration – Comfortable working across multiple teams, geographies, and functions, including architects, engineers, product owners, and business users
Problem Solving – Strong analytical skills and a solution-oriented mindset for complex data challenges
13+ years of experience in data engineering, big data platforms, and cloud-based infrastructure
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related technical discipline
Proven track record in building production-grade data platforms using Iceberg, Spark, and AWS services
Deep understanding of federated architectures, hybrid integration patterns, and metadata-driven pipelines

Additional Information:

Job Posted:
May 17, 2025

Employment Type:

Fulltime

Work Type:

On-site work

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Vice President - Data Architecture VP