Title: Data Analyst/EDW Solution Architect
Location: San Jose, CA
Work Type: Onsite 5 days
C2C or W2
Couple of re points: Client is seeking below & role is based out of San Jose USA - 5 working days from the HQ office.
Tech Stack: The role requires strong hands-on experience in SQL, Python, Informatica, APIs, reporting, and data engineering. Candidate needs to be able provide sufficient practical examples of building integrations, designing reports/dashboards, working with ERP/CRM systems (Workday/Salesforce), or solving real-world technical challenges.
Domain Knowledge: Please prioritize candidates with experience on both the engineering and business sides, specifically:
A solid grasp of SaaS financial metrics such as ARR, bookings, billings, revenue, and pipeline.
Hands-on work building data models and reports for these metrics, including aligning definitions across Finance, Sales, and RevOps systems like Salesforce and Workday.
Direct experience partnering with senior leaders in Finance, FP&A, and RevOps to gather requirements, agree on metric definitions, and deliver reporting the business trusts.
we're looking for candidates with:
- Strong hands-on experience in SQL, Python, Informatica, and API integrations
- Data architecture and pipeline design experience
- Reporting and dashboard development experience with measurable business outcomes
- Strong stakeholder management and requirements gathering skills
- Experience with Workday/Salesforce data (preferred)
- AI/LLM experience (nice to have)
We can look at architect and senior data engineer roles with solutioning expertise.
JD:
Data Analyst/EDW Solution Architect
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. Serving as the face of IT for business stakeholders, this individual will engage with them regularly to understand priorities, shape solutions, communicate progress, and drive adoption. The role will use Informatica for the data ingestion and integration layer, Google BigQuery as the cloud data warehouse and data lake platform, and Tableau as the analytics and visualization user interface.
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.
-
Technical leadership: Lead design reviews, create architecture standards and technical documentation, mentor team members, and collaborate with application, cloud, security, and business teams.
Required Qualifications
-
Bachelor's degree in Computer Science, Information Systems, Data Engineering, Analytics, or a related field, or equivalent practical experience.
-
8+ years of experience across data engineering, business intelligence, data analysis, data warehousing, or solution architecture.
-
Hands-on experience with Informatica products and enterprise ETL/ELT design, development, deployment, and support.
-
Strong experience with Google BigQuery, SQL, cloud data warehousing, data lake concepts, data modeling, and query optimization.
-
Demonstrated experience developing Tableau dashboards, semantic layers, calculated fields, data sources, row-level security, and performance-optimized visualizations.
-
Experience building AI-enabled solutions on enterprise data warehouse or data lake platforms, including secure access to governed data for AI models, agents, or applications.
-
Hands-on experience designing and implementing Role-Based Access Control (RBAC) and Row-Level Access (RLA) security controls across BigQuery, Tableau, and enterprise data products.
-
Strong knowledge of dimensional modeling, star and snowflake schemas, slowly changing dimensions, master and reference data, and data lifecycle management.
-
Experience integrating structured and semi-structured data from SaaS applications, relational databases, APIs, and files.
-
Proficiency in SQL and at least one scripting or programming language such as Python.
-
Experience with data quality frameworks, metadata management, data lineage, testing, CI/CD, and production support.
-
Strong communication skills with the ability to explain technical concepts to business audiences and convert business requirements into scalable solutions.
-
Proven ability to serve as the face of IT for business teams, build trusted stakeholder relationships, lead recurring working sessions, and communicate solution strategy, trade-offs, risks, and delivery status clearly
