Senior Solutions Architect (Data)

Sr. Solution Architect (Data)FTELocation: 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 summaryWe’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 responsibilitiesDefine 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.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, BigQuery, Redshift, Databricks, or similar.Proven track record in data modeling (dimensional/3NF), 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, GraphQL, SOAP) and familiarity with education interoperability standards (OneRoster, 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 / PreferredPrior experience in EdTech, education data projects, or working with school/district customers. (Knowledge of Ed-Fi, OneRoster, 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, DataHub, Collibra).Familiarity with GDPR, FERPA, state education data privacy regulations.Experience with CI/CD for data (GitOps 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 / BigQuery / 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).

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