OverviewWorking within enterprise architecture and security standards and alongside modern full-stack engineers, including React/TypeScript developers, this person translates product requirements into scalable, secure, well-instrumented data services. The ideal candidate combines hands-on database and platform depth with architectural judgment, operational ownership, and a bias toward automation and incremental delivery.
ESSENTIAL DUTIES AND RESPONSIBILITIESApplication Data Architecture and Engineering- Own the architecture and evolution of the application data layer, including logical and physical models, schemas, storage strategies, access patterns, service boundaries, and technology selection.
- Design transactional and operational models that preserve integrity, support concurrency and workflow state changes, and appropriately balance normalization, auditability, and performance.
- Model identity, authentication, and authorization data with security and application teams, including users, roles and permissions, sessions or token metadata, login events, account status, and audit history.
- Design application-utilization and product-telemetry models for events, feature usage, workflow progression, adoption, errors, and performance, with appropriate privacy and retention controls.
- Design and implement, or guide implementation of, application-facing APIs and data services with clear contracts for validation, pagination, filtering, versioning, idempotency, errors, and backward compatibility.
- Design caching and shared-state strategies using Redis or comparable technologies, including keys, time-to-live policies, invalidation, consistency, graceful degradation, and observability.
- Own database and query performance through schema design, indexing, execution-plan analysis, partitioning, connection pooling, ORM and query-pattern review, N+1 prevention, and capacity planning.
- Establish standards for schema evolution, migrations, seed and reference data, rollback, compatibility, and zero- or low-downtime deployment.
- Define safe synchronization between operational application stores and analytical platforms through change data capture, events, replication, and backfill patterns that protect application performance.
- Evaluate data stores, API infrastructure, and supporting services for scalability, availability, recoverability, security, maintainability, performance, and cost.
Data, Reliability, and Observability- Implement and continuously improve data connectors, ingestion jobs, and orchestration workflows according to established enterprise patterns.
- Build and maintain CI/CD for data pipelines, database migrations, APIs and data services, and environment configuration across development, staging, and production.
- Own the production lifecycle of application data services and ingestion systems, including on-call participation, alert tuning, incident response, root-cause analysis, and corrective action.
- Implement automated data-quality, schema, and contract checks at ingestion and application-service boundaries.
- Monitor and alert on pipeline health, freshness, database availability and performance, query and API latency, error rates, connection pools, cache health, replication lag, and application data quality.
- Define and test backup, restore, disaster-recovery, retention, load-testing, and capacity-planning procedures aligned with service objectives.
- Maintain runbooks, architecture diagrams, data dictionaries, data contracts, migration procedures, and infrastructure-as-code automation that reduce drift and manual intervention.
Shared Responsibilities (Cross-Team Collaboration)- Partner with Product and Application Engineering to translate workflow and user-experience requirements into durable data models, APIs, and operational data services.
- Work effectively with React/TypeScript and other full-stack engineers by understanding client data consumption, state-management needs, API behavior, and frontend performance implications well enough to design practical interfaces.
- Partner with Data Engineering on backfills, schema evolution, change data capture, operational-to-analytical movement, downstream quality assertions, and safe use of application data for reporting.
- Partner with Security and Platform Engineering on identity-provider integrations, OAuth 2.0 and OpenID Connect patterns, secrets, encryption, network controls, least-privilege access, and environment configuration.
- Lead architecture, data-model, API-contract, and code reviews; communicate technical decisions, tradeoffs, risks, incidents, and migration plans clearly across teams.
Process and Standards- Use Git with pull requests, protected branches, required reviews, automated checks, and traceable release practices.
- Establish automated tests for database migrations, data contracts, APIs, integrations, performance, and data quality based on component risk.
- Build small, modular, backward-compatible components that favor fast feedback and safe deployment over monolithic frameworks.
- Apply secure-by-design, observability, service-level, and DataOps practices that improve cycle time, reliability, performance, and operational clarity.
REQUIRED QUALIFICATIONSTechnical Skills and Experience- Strong experience architecting, building, and operating production application data layers, databases, data services, and ingestion systems.
- Advanced SQL and relational database experience, with strong logical and physical modeling skills for transactional and operational workloads.
- Hands-on experience with transactions, consistency, concurrency, indexing, query plans, partitioning, connection management, and production query optimization.
- Experience designing and implementing application-facing APIs or data-access layers, including RESTful APIs and/or GraphQL, contracts, versioning, validation, and error semantics.
- Experience designing and operating Redis or comparable caching, including invalidation, time-to-live policies, consistency, and failure handling.
- Working knowledge of identity and authentication architecture and data, including OAuth 2.0, OpenID Connect, single sign-on, role-based access, sessions or tokens, login events, and audit trails.
- Experience modeling application events, utilization, telemetry, and operational metrics and integrating operational data safely with analytical systems.
- Familiarity with modern full-stack architecture and effective collaboration with React/TypeScript developers and backend engineers; deep frontend implementation expertise is not required.
- Hands-on experience with CI/CD, automated database migrations, cloud platforms, managed databases and caches, infrastructure as code, monitoring, tracing, incident management, and Git-based review workflows.
Professional Skills- Demonstrated architecture and ownership mindset, with accountability for production data services and explicit technical tradeoffs.
- Ability to move between architecture, hands-on implementation, design and code review, troubleshooting, and operational support.
- Ability to work effectively across Application Engineering, Data Engineering, Platform, Security, Product, and operational teams.
- Strong communication and documentation skills, with a pragmatic bias toward automation, measurable reliability, incremental delivery, and maintainability.
Preferred Qualifications- Experience with event-driven systems, message queues or streaming, change data capture, and asynchronous workflow patterns.
- Experience with containers, API gateways, serverless or managed application platforms, and distributed-system observability.
- Experience supporting applications that handle sensitive or regulated data and require strong auditability and access control.
- Experience connecting operational application data to cloud warehouses, lakehouses, semantic layers, business intelligence, or product analytics.
EDUCATION AND EXPERIENCE- Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
- Senior-level experience in DataOps, Platform Engineering, Database Engineering, Backend Engineering, Application Data Engineering, Data Engineering, or a closely related role.
- Demonstrated experience supporting production applications or data services with meaningful availability, security, performance, and recovery expectations.
