Engineering & Delivery Lead - Data Services

Citigroup; Pune District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Citigroup in Pune seeks a highly accomplished SVP - Engineering & Delivery Lead (Data Services) to own the technical delivery, architecture alignment, and global execution of our data platforms. You will lead distributed agile teams, drive AI‑first software delivery, modernize data pipelines and lakehouse infrastructure, and ensure compliance with enterprise standards.

The role requires hands‑on leadership, capacity planning, talent development, and alignment of engineering work with target

Qualifications

• 20+ years of software/data engineering experience (senior leadership preferred).
• Proven track record in managing distributed teams and delivering data platforms.
• Strong expertise in data pipelines, streaming, and data lakehouse architectures.

Responsibilities

• Engineering Leadership & People Management: Lead distributed software and data engineering teams, with performance evaluations.
• Architectural Alignment & Technical Governance: Ensure alignment with target architecture and design patterns; oversee reviews.
• AI-First Software Delivery: Champion AI-first delivery using generative tools to accelerate development and improve quality.
• End-to-End Technical Delivery: Own the delivery of data services, real-time pipelines, and platform integrations from inception to production.
• Engineering Excellence: Enforce CI/CD, automated testing, and high-quality software practices.

Skills

People management

Agile delivery leadership

Architectural governance

AI-first mindset

Data services & lakehouse

Tools

Java/Spring Boot

GitHub Copilot

Apache Ranger

Job description

We are seeking a highly accomplished, hands-on SVP - Engineering & Delivery Lead (Data Services) to join our technology leadership team in Pune. In this critical engineering role, you will serve as the Platform Tech Lead and take end-to-end ownership of the technical delivery, architectural alignment , and global engineering execution for our strategic Data Services platforms.

This is a senior software engineering leadership and technical delivery role designed for a seasoned software/data engineer with a proven track record of managing engineering teams and technically steering agile workstreams. In this role, you will hold direct line management responsibility for distributed agile engineering pods, providing people leadership, talent development, and technical oversight.

You will be responsible for driving the technical execution of key initiatives, including modernizing our core data services, scaling our data lakehouse infrastructure, and engineering critical regulatory-driven technology programs, compliance commitments, and enterprise technology mandates. You will own team capacity planning, hiring, talent development, and performance evaluations.

A core expectation of this role is an AI-First Thinking Mindset . You will actively champion and drive the adoption of generative AI tools (such as GitHub Copilot, Claude, ChatGPT, and other developer productivity assistants) to significantly accelerate software delivery, automate testing, and improve code quality across your teams, adapting seamlessly to the enterprise-approved tools available within our network. You will ensure that all engineering deliverables strictly align with our target architecture, enforce rigorous code and design standards, and maintain hands‑on technical oversight and architectural alignment across multiple global agile engineering workstreams.

Key Responsibilities

1. Engineering Leadership & People Management
   • Engineering Line Management: Manage, hire, develop, and conduct performance evaluations for a distributed, multi-location team of software and data engineers, ensuring continuous talent growth and high team engagement.
   • Agile Pod Delivery: Provide hands‑on technical leadership and functional management across agile engineering pods, driving daily sprint execution, code reviews, and architectural alignment.
   • AI-First Software Delivery: Champion and drive an AI‑first developer culture. Promote the adoption of generative AI coding assistants and modern productivity tools to accelerate software development, automate unit test generation, and streamline code refactoring across your engineering teams.
   • End-to-End Technical Delivery: Take full accountability for the technical delivery of data services, real‑time pipelines, and platform integrations from inception to production deployment.
   • Engineering Excellence: Foster a culture of high‑quality software engineering, enforcing rigorous unit testing, automated integration testing, and continuous integration/continuous delivery (CI/CD) practices.
2. Architectural Alignment & Technical Governance
   • Architectural Adherence: Ensure all engineering deliverables and system designs strictly align with the target enterprise architecture, design patterns, and future‑state roadmaps defined by the Enterprise Architecture teams.
   • Technical Design & Review: Lead the technical implementation design of platform components, APIs, and data access patterns, ensuring they are optimized for high performance, low latency, and scalability.
   • Technical Debt Management: Proactively identify and remediate technical debt, ensuring the platform remains maintainable, resilient, and sustainable.
   • Security & Governance by Design: Enforce strict data security, row/column‑level masking, and access control policies (e.g., Apache Ranger) within all engineered solutions.
   • Database Security Compliance: Ensure that all data storage and pipeline implementations adhere to rigorous enterprise security standards, including Transparent Data Encryption (TDE), secure connection protocols, and continuous database auditing.
3. Platform Modernization & API Engineering
   • Data Pipeline Engineering: Oversee the engineering of robust, high‑throughput data pipelines across hybrid relational databases and modern cloud‑native lakehouses.
   • API & Microservices Development: Lead the development of standardized, secure, and resilient microservices (primarily Java/Spring Boot) to support high‑concurrency data consumption and AI‑driven use cases.
4. Regulatory & Mandatory Engineering Commitments
   • Regulatory Engineering: Lead the technical execution of critical regulatory‑driven technology programs, compliance commitments, and enterprise technology mandates, ensuring engineered solutions are robust, compliant, and delivered within strict timelines.
   • Audit‑Ready Standards: Ensure all technical documentation, system designs, and deployment pipelines meet rigorous internal audit and regulatory compliance standards.

Technology Skills & Competencies

Required Te