Senior Data Architect

Job TitleSenior Data Architect (Enterprise)About the RoleWe are seeking an experienced Solution Architect (Data) to lead design and delivery of enterprise data & analytics solutions.As a key member of our team, you will be responsible for owning architecture for ETL/ELT, data warehousing, analytics pipelines, data governance, and integrations with education systems.Our ideal candidate will have 12–15 years of experience in data engineering, analytics, or data architecture roles with progressive ownership.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.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.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).How to ApplySend your resume and a cover letter to us via email. If we think you're a good fit, we'll reach out to discuss further.