Lead Data Engineer

Overview

Lead Data Engineer supporting the Relationship Manager Transformation programme, building the data and AI foundation for Commercial Banking. The role creates trusted data products, real-time insights, and AI-ready platforms for CRM, servicing, and relationship management.

What you'll do

• Design, develop, and maintain complex Data Products using clean, maintainable, and efficient solution design following best practices.
• Lead implementation reviews and all aspects of data product delivery to preserve quality and share knowledge.
• Lead a talented group of engineers, guiding and working alongside them across the entire software development lifecycle.
• Manage delivery of robust, scalable data applications and features.
• Evaluate and recommend tools, technologies, and processes to ensure the highest quality product platform.
• Identify and implement best practices for data engineering.
• Resolve complex data issues, technical problems, and bugs using problem-solving and analytical skills.
• Provide guidance and mentorship to engineers.
• Ensure data security through secure architectural practices.
• Apply DevOps practices and CI/CD pipelines.
• Manage tasks and priorities effectively using Agile methodology to ensure timely delivery.
• Communicate effectively with the team and stakeholders.
• Perform custodianship governance activities on data assets that the platform produces and consumes.

What you'll need

• 17-22 years of experience.
• Experience developing data validation methodology and data hub process models, including sourcing, loading, transformation, and extraction in alignment with Group and business needs.
• Ability to align data models to domain boundaries and real access patterns across services, streams, and warehouses.
• Ability to design for evolvability using additive changes, backward-compatible schemas, and safe deprecations.
• Ability to embed data quality checks, define conformed dimensions and a semantic layer, and implement privacy and security controls such as row/column-level security and PII handling.
• Experience coaching others and enforcing standards through reviews and reusable templates.
• Experience leading teams to identify issues and improve automation across the end-to-end application development lifecycle.
• Experience using technology stack and tooling to evolve applications at pace and ensure efficiency, quality, and security is monitored as part of every build.
• Holistic understanding of Python and the ability to make intuitive decisions in familiar contexts.
• Ability to implement multi-threading and asynchronous programming using tools like threading and asyncio.
• Ability to tune complex SQL queries and workloads; design schemas and constraints; manage concurrency/isolation; refactor for performance and readability; and mentor others.
• Ability to build, inspire, and scale high-performing Data Engineering, Analytics, and Modelling teams.
• Ability to create a culture of ownership, innovation, and continuous improvement through effective coaching, mentoring, talent development, and servant leadership.
• AI Literacy.
• Data Architecture.
• Quality Engineering.
• Agile Methodology & Tools.
• Expertise in FinOps/Optimisation for Cloud Computing.
• Google Analytical Database technologies, including Big Query, Cloud SQL, Spanner, and AlloyDB.
• Infrastructure as Code experience.
• Knowledge and utilisation of streaming platforms such as Pub/Sub or Kafka, and technologies such as Dataflow and Flink.
• Ability to build and deploy container-based solutions using GKE.
• Experience building solutions to provide Data Quality using Dataplex, Atacama, or similar tools.
• Exposure and experience with modern programming practices, including Functional programming and Event-based solutions.
• Communication.
• Customer centricity.
• Critical thinking.
• Data Literacy.
• Data Storytelling.

Details

• Location: Hyderabad Knowledge Park Tower 2.
• Work mode: Hybrid.