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 / Ed Tech 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 (One Roster, 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.

Support pre-sales and RFP responses with technical solutioning and estimations when required.

Champion best practices for observability (metrics, logging), testing, and cost governance in data platforms.

Must-have skills & experience (non-negotiable)

12–15 years in data engineering, analytics, or data architecture roles with progressive ownership.

Hands-on experience building and operating ETL / ELT pipelines and orchestration frameworks (Airflow, dbt, Talend, Informatica, or equivalent).

Strong design and operational experience with cloud data platforms (AWS / GCP / Azure) — data warehouses / lakes such as Snowflake, Big Query, Redshift, Databricks, or similar.

Proven track record in data modeling (dimensional / 3 NF), master data management, schema design, and query performance optimization.

Experience with streaming technologies (Kafka, Kinesis, Pub / Sub) and hybrid batch / streaming patterns.

Familiar with BI / analytics tooling and self-service analytics (Tableau, Power BI, Looker, Superset) and delivering dashboards / reports to non-technical stakeholders.

Strong knowledge of data security, privacy, and governance frameworks (encryption, RBAC, GDPR / FERPA implications for education data).

Solid API and integration experience (REST, Graph QL, SOAP) and familiarity with education interoperability standards (One Roster, Ed-Fi, LTI) is highly desirable.

Excellent communication skills — able to present technical concepts to product, sales, and executive stakeholders.

Proven leadership : mentoring, technical decision making, and running architecture review boards.

Nice-to-have / Preferred

Prior experience in Ed Tech, education data projects, or working with school / district customers. (Knowledge of Ed-Fi, One Roster, SIS / LMS systems is a plus.)

Experience building or operating AI / ML pipelines and MLOps for predictive analytics (student success models, recommendation engines).

Experience with data cataloging / lineage tools (Great Expectations, Amundsen, Data Hub, Collibra).

Familiarity with GDPR, FERPA, state education data privacy regulations.

Experience with CI / CD for data (Git Ops for pipelines, automated testing for data).

Previous role in consulting / solutions architecture working directly with customers on design and implementation.

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

Cloud : AWS / GCP / Azure (production experience).

Data storage / compute : Snowflake / Big Query / Redshift / Databricks / S3 / GCS.

Orchestration / ETL : Airflow, dbt, Prefect, Informatica, Talend, or custom pipelines.

Streaming : Kafka, Kinesis, Pub / Sub.

BI & analytics : Tableau, Power BI, Looker, Superset.

Data ops & governance : Great Expectations, Data Catalogs, lineage tools.

Dev tools : Git, Terraform, Docker, Kubernetes, CI systems.

Languages : SQL (expert), Python, Scala / Java (optional).