Senior Solutions Architect

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-onSolution 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. 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 / Preferred Prior 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).