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Senior Solutions Architect (Data)
Senior Solutions Architect (Data)Hillview Consulting Solutions • Bangalore, IN
Senior Solutions Architect (Data)

Senior Solutions Architect (Data)

Hillview Consulting Solutions • Bangalore, IN
8 days ago
Job description

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.
  • 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).
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