Solution Architect - Informatica/Google BigQuery

Position Summary:

We are seeking an experienced Data Analyst/Enterprise Data Warehouse (EDW) Solution Architect to design, build, and optimize scalable enterprise data, analytics, and AI solutions. This blended role will translate business needs into trusted data products, engineer reliable ingestion and transformation pipelines, and define the architecture for a modern data warehouse and data lake ecosystem.

Key Responsibilities:

• Solution architecture: Define the target-state EDW, data lake, and analytics architecture, including logical and physical data models, integration patterns, security controls, metadata, lineage, and nonfunctional requirements.

• Data ingestion and integration: Design and develop batch and near-real-time pipelines using Informatica to ingest data from enterprise applications, databases, APIs, files, and third-party platforms.

• BigQuery engineering: Build and optimize curated data layers, dimensional models, data marts, and lakehouse-style datasets in Google BigQuery, with attention to partitioning, clustering, performance, scalability, and cost.

• Data transformation: Implement reusable transformation logic, data standardization, reconciliation, and orchestration processes across raw, trusted, and consumption layers.

• Analytics and visualization: Partner with business stakeholders to define KPIs and create governed Tableau dashboards, reports, and self-service analytics experiences.

• Business analysis: Elicit and document requirements, profile source data, perform exploratory analysis, identify trends and anomalies, and translate findings into actionable recommendations.

• Data quality and governance: Establish data quality rules, monitoring, exception handling, lineage, reference data, business definitions, stewardship processes, and auditability.

• Security and compliance: Apply role-based access, least-privilege principles, sensitive-data protections, retention requirements, and applicable privacy and regulatory controls.

• AI solutions on the EDW: Design and build AI-enabled solutions that securely use governed EDW and data lake assets, implementing Role-Based Access Control (RBAC) and Row-Level Access (RLA) controls to ensure users, applications, and AI services can access only authorized data.

• Business-facing IT leadership: Act as the primary IT partner and trusted advisor for business stakeholders, maintaining frequent interaction to understand needs, facilitate decisions, manage expectations, present solution options, and coordinate delivery across technical teams.

• Operational excellence: Monitor pipelines and dashboards, troubleshoot production issues, conduct root-cause analysis, and improve reliability through automation, testing, and observability.