Data Architect - Big Data/Data Warehousing

Responsibilities :

- Drive the data architecture, data modelling, design, and implementation of data applications using standard open-source big data tech stack, Data Warehouse / MPP databases, and distributed systems.

- Gather business and functional requirements from external and/or internal users, and translate requirements into technical specifications to build robust, scalable, supportable solutions. Participate and drive the full development lifecycle.

- Build the Standards and best practices around a Common Data Model and Architecture, Data Governance, Data Quality, and Security for multiple business areas across Myntra.

- Collaborate with platform, product, and other engineering and business teams to evangelise those Standards for adoption across the org.

- Mentor data engineers at various levels of seniority by doing their design and code reviews, providing constructive and timely feedback on code quality, design issues, and technology choices, with performance and scalability being critical drivers.

- Manage resources on multiple technical projects and ensure schedules, milestones, and priorities are compatible with technology and business goals.

- Setting up best practices to help the team achieve the above and constantly thinking about improving the technology use are your responsibilities.

- Driving the adoption of these best practices around coding, design, quality, and performance in your team.

- Stay abreast of the technology industry, market trends in the field of data architecture and development.

- Demonstrates understanding of data lifecycle (data modelling, processing, data quality, data evolution) and underlying tech stacks (Hadoop, Spark, MPP).

- Drives setting data architecture standards encompassing the complete data life cycle (ingestion, modelling, processing, consumption, change management, quality, anomaly detection).

- Challenge the status quo and propose innovative ways to process, model, and consume data when it comes to tech stack choices or design principles.

- Implementation of long-term technology vision for your team.