Senior Solutions Architect (Data)

Sr. Solution Architect (Data)

FTE

Location : Remote is okay

If candidate is in Mumbai this would be onsite in Andheri East, Mumbai, Maharashtra

Experience : 12–15 years

Start : End of December (urgent)

Role summary

We’re looking for a senior, hands-on Solution Architect (Data) to lead design and delivery of enterprise data & analytics solutions. You’ll own architecture for ETL / ELT, data warehousing, analytics pipelines, data governance, and integrations with LMS / EdTech systems — turning education data into actionable insights and production-grade platforms used by districts, schools, and publishers.

This is a highly technical role requiring 12–15 years of experience, proven leadership in data architecture, deep ETL / analytics know-how, and familiarity with education data ecosystems or similarly regulated verticals.

Key responsibilities

• Define end-to-end data architecture and roadmaps for large-scale education data platforms (ingestion → storage → modeling → serving → analytics / ML).
• Lead design and implementation of robust ETL / ELT pipelines and orchestration (batch + streaming) to bring together disparate education systems (LMS, SIS, assessment, content platforms).
• Design and optimize data warehouses / data lakes (schema strategy, partitioning, performance, cost).
• Drive integration patterns and APIs for interoperability (OneRoster, Ed-Fi, LTI, custom APIs), and lead vendor / partner integrations.
• Establish data governance, privacy, lineage, and security practices suitable for student data (PII handling, role-based access, encryption, audit).
• Collaborate with product managers, engineering leads, data scientists, and customer success to translate customer needs into deliverable solutions.
• Produce architecture artifacts : solution blueprints, CI / CD patterns for data delivery, runbooks, and SLA / operational playbooks.
• Mentor engineering and data teams;

run architecture reviews and technical critiques.

Must-have skills & experience (non-negotiable)

Nice-to-have / Preferred

Technical stack (examples we expect you to be comfortable with)