[Remote] Principal Data Platform Engineer

Note: The job is a remote job and is open to candidates in USA. Doma Technology LLC offers innovative solutions for the real estate industry, making closings simpler and more efficient. They are seeking a Principal Data Platform Engineer to oversee the migration to a new cloud environment and modernize data management processes, ensuring data is accurate, governed, and ready for use by various teams.ResponsibilitiesDesign and implement end-to-end data architecture including application CDC, streaming, schema design, transformation, warehouse/mart modeling, and consumption-readiness with IaC and automation-first deliveryBuild resilient multi-region database and replication topologies with automated failover and DRArchitect streaming pipelines with correctness, replayability, and schema evolution as first-class concernsModel, document, and catalog marts for downstream self-service analytics and customer-facing consumptionBuild monitoring, alerting, and data-quality observability across data platform servicesOwn PII classification, lineage, access controls, and encryption in partnership with SecurityMentor engineers and set architectural standards across data platform craftTreat compute and storage spend as a design inputSkills8+ years in data engineering, platform engineering, SRE, or DevOps, with a track record at Staff or Principal IC levelProven experience building large-scale distributed data systems in productionDeep hands-on cloud experience (Azure preferred; AWS/GCP transferable) with IaC and CI/CD (Terraform or comparable)Strong SQL and data modeling fundamentals across streaming and relational/warehouse patternsProduction depth in at least one orchestration tool and one streaming/ingestion stackExperience designing cross-regional database replication architectures, including failover and consistency trade-offsWarehouse and mart modeling with a transformation/semantic layer (dbt or comparable)Proficiency in Python, Go, or similar for automation and toolingTrack record of owning ambiguous, cross-team problems end to end from approach through deliveryKubernetes for data workloads or equivalent container orchestrationTable/lakehouse formats (Iceberg, Delta, Hudi) and judgment on where they fit against a warehouseData-quality frameworks (Great Expectations, Soda) and production observability (Prometheus, Grafana, Datadog)Schema registries and event contracts (Avro, Protobuf, JSON Schema)Catalog and discovery tooling (Microsoft Purview, DataHub, Collibra, or similar)GitOps tooling (Flux, ArgoCD) and FinOps practicesPractical data governance: PII identification, lineage, encryption, and a sane access model for regulated dataFamiliarity with MCPs (Model Context Protocol) and exposing data to AI systems safelyBackground in fast-paced, high-growth environments with hard delivery deadlinesBenefitsBonus & EquityMedical/dental/vision insurance401(k)Generous vacation timePaid bonding leavePaid Time Off (PTO)12 Weeks of Paid Family Bonding Leave (Maternity and Paternity)Incredible medical, dental, and vision benefits options to allow you to customize to you and your family’s needs that all start in the following month following your first day of employmentHealth Savings Account (HSA)401K with company match programShort-Term &