Lead Data Architect

Experience: 10+ Years

Responsibilities:

Build strong technical relationships with customer technology SMEs, actively engaging in the co-creation of innovative solutions in areas such as Modern Data Technologies like Spark, KAFKA, NoSQL DBs, Real time streaming and analytics etc. and strong conceptual knowhow of GenAI / ML based data quality solutioning.

Strong experience in Data Lake, Data Warehouse, ET:L and BI concepts.

Serve as a trusted advisor by consistently demonstrating technical depth and earning the confidence of highly skilled technical stakeholders.

Lead the technical and functional understanding of a large-scale e-commerce platform, driving the implementation of structural solutions across design, development, testing, and deployment phases.

Report directly to the Program Director, acting as a key technical SME within the program.

Own the technical excellence of software development processes, with a strong focus on:

Code quality and best practices

Automation and CI/CD

Management of technical debt, structural changes

Provide technical leadership, including:

Mentoring and developing engineering talent

Defining and guiding the technical direction and architecture

Ensuring timely delivery of scalable and high-quality solutions

Making strategic decisions related to the technology stack and infrastructure

Design and implement robust technical processes for proactive identification, monitoring, and assurance of data quality across a large-scale data engineering infrastructure, tightly integrated with a microservices-driven transactional platform.

Core Skills:

Proven hands-on experience in managing and building large-scale distributed data platforms, including Data Lakes, Data Warehouses (DWH), ETL pipelines, BI reporting solutions, and data delivery for business and finance functions

Strong domain knowledge and experience in financial data reconciliation processes within Data Lake/DWH environments

Expertise in both batch and real-time data analytics infrastructure and operations, preferably using cloud platforms like AWS or Azure

Proficient in open-source technologies such as Apache Spark, Python, and enterprise tools including Oracle

Exposure / experience in working with a Microservices based platform