Senior Data Architect

📋 Description

• • Own the end-to-end design of Trueplatform’s next-generation data architecture, creating a unified, multi-tenant data warehouse that powers analytics for hundreds of growth-stage and Fortune 1000 clients across North America, EMEA, and APAC.
• • Architect a cloud-native data warehouse on Snowflake (preferred) or Redshift that supports both high-volume transactional ingestion and sub-second analytical queries, while enforcing strict tenant isolation and enabling cross-tenant benchmarking where clients opt in.
• • Model dimensional schemas, slowly changing dimensions, and fact tables that serve product, finance, marketing, and executive search teams—translating complex business questions into scalable star and snowflake designs.
• • Build an enterprise-grade integration framework that consumes data from 30+ external HRIS, ATS, CRM, and survey platforms via REST/GraphQL APIs, webhooks, SFTP, and streaming Kafka topics; ensure every integration is observable, idempotent, and recoverable.
• • Establish an event-driven, CDC-based pipeline using AWS MSK and Lambda that synchronizes operational PostgreSQL changes into the warehouse in near real-time, reducing latency from hours to minutes and enabling live dashboards for client success managers.
• • Create a self-service analytics layer—leveraging dbt for transformation, Airflow for orchestration, and Sisense for visualization—that empowers non-technical stakeholders to define metrics, schedule refreshes, and build executive-ready dashboards without ticket queues.
• • Define and enforce data governance policies covering PII masking, GDPR/CCPA compliance, role-based access control, and field-level lineage; partner with Legal & Security to pass SOC 2 Type II and ISO 27001 audits.
• • Design cost-optimization guardrails that leverage Snowflake’s auto-suspend, materialized views, and query-result caching to keep warehouse spend under 5 % of ARR while supporting 10× data growth over the next three years.
• • Lead zero-downtime migration of legacy Redshift and RDS snapshots into the new architecture, scripting Terraform modules and Python migration notebooks that validate row counts, checksums, and referential integrity across 5 TB of customer data.
• • Mentor a distributed team of data engineers and analytics engineers, instituting code-review standards, CI/CD pipelines, and architectural decision records (ADRs) that raise the bar for data quality and engineering excellence.
• • Collaborate daily with Product Managers to translate roadmap epics into technical blueprints, ensuring every feature—from diversity analytics to predictive attrition models—has a clear data contract and scalable ingestion path.
• • Champion a culture of experimentation by establishing feature-flagged schema changes, A/B test datasets, and sandbox environments where analysts can safely prototype new KPIs before promoting them to production.