Data Analytics Solutions Architect (Manager Level)

Role: Data Analytics Solutions Architect (Manager Level)

Location: New York, NY

Duration: 6+ Months

MOI: Video

Job Description:

experience level- Senior / Manager Level (7+ Years Minimum)

compliance mandate- Mandatory WebEx Video Internal Screening + Verifiable Lead/Manager References Required.

Critical Sourcing Anchor (The Blended Visualization & Event-Stream Filter):

The Key Filter The Hybrid Viz & Data Pipeline Architect:

Move past standalone business intelligence (BI) report developers who only work downstream in visualization tools. This Manager-level role demands a true Data Solutions Architect who acts as a critical link between business leadership and the data engineering team.

Sourcing must isolate profiles demonstrating a dual expertise: advanced data modeling and reporting mastery within Power BI (DAX, Power Query, semantic modeling), perfectly blended with an understanding of modern distributed data infrastructure.

The candidate must have experience designing upstream ETL/ELT data pipelines, consuming API-based integrations, and architecting workflows within real-time, event-driven streaming frameworks like Apache Kafka ideally deployed over Google Cloud Platform (Google Cloud Platform) data engines.

Position Summary:

We are seeking a high-caliber, stakeholder-facing Data Analytics Solutions Architect to govern the design, delivery, and scalability of our enterprise reporting and data integration ecosystems. Operating at a Manager level, you will serve as the principal interface between executive business units, analytics divisions, and core data engineering squads.

You will translate complex corporate objectives into production-grade solution designs overseeing everything from semantic dataset layers and Power BI dashboard architectures to real-time event streams and orchestrators. This role requires an ideal mix of visual analytics mastery, structural data tracking, and agile delivery management.

Key Responsibilities:

• Enterprise Architecture Modeling: Design and construct robust, enterprise-grade Power BI dashboards, reports, unified datasets, and performant semantic models utilizing optimized DAX and Power Query frameworks.
• Streaming & Integration Design: Blueprint and support data integration patterns utilizing ETL/ELT architectures, REST APIs, and real-time, event-driven streaming environments (e.g., Apache Kafka).
• Cloud Pipeline Collaboration: Partner directly with engineering teams to map scalable pipelines and optimize structured and unstructured data flows, preferably across Google Cloud Platform (Google Cloud Platform).
• Orchestration & Workflow Governance: Define, document, and monitor end-to-end data workflows, job scheduling boundaries, and complex pipeline orchestration models.
• Cross-Functional Agile Leadership: Lead requirements-gathering workshops, author precise solution design and data mapping blueprints, facilitate User Acceptance Testing (UAT), and drive scrum velocities within Agile delivery tracks.
• Data Quality Optimization: Champion data governance baselines to proactively identify and fix performance bottlenecks, indexing issues, and anomalies in data quality.

Required Technical Skills & Qualifications:

• Tenure Foundation: Minimum 7+ years of dedicated professional experience navigating Business Intelligence, Analytics Architecture, and Data Engineering environments.
• Power BI Subject Matter Authority: Exceptional, deep-dive data modeling skill sets; expert-level proficiency writing highly optimized, complex DAX calculations and configuring enterprise-scale semantic layers.
• Event-Driven & API Literacy: Direct experience architecting or integrating solutions that consume data from Kafka topics and API endpoints.
• Cloud Platform Exposure: Hands-on architectural familiarity with modern cloud data warehouses, data lakes, and services (with a strong preference for Google Cloud Platform).
• Stakeholder Delivery Management: Proven background managing demanding business stakeholders, leading UAT validation phases, and driving engineering teams as a technical manager.
• Onsite Commitment: Uncompromised ability to work onsite in the New York City office 3 days per week.

Preferred Sourcing Attributes:

• Comprehensive knowledge of enterprise data governance, master data management (MDM), and metadata lineage tracking.
• Blended expertise managing both high-volume batch scheduling processing and ultra-low latency real-time streaming architectures.

Architectural Litmus Test & Screening Gates:

Incorporate these specific engineering questions into your mandatory WebEx video screening before presenting candidates:

1. Power BI Semantic Architecture: "When designing a Power BI semantic model for an enterprise client with hundreds of millions of rows of data across multiple business domains, how do you structure your tables? Explain your approach to balancing Import vs. DirectQuery modes, and how you optimize slow-running DAX measures."
2. Kafka Event-Driven Ingestion: "Walk me through how you have integrated an event-driven system like Apache Kafka into an analytics layer. How do you handle schema evolution, and what structures do you establish to ensure real-time Kafka streams translate cleanly into historical reporting tables?"
3. Google Cloud Platform Pipeline Design & Orchestration: "Describe a Google Cloud Platform-based analytics architecture you've worked with. What native tools or open-source orchestrators (e.g., Airflow/Cloud Composer) did you select to handle job scheduling, error handling, and data dependencies between your ETL phases?"
4. Managing Technical Handoffs: "As an architect operating at a Manager level, how do you handle a situation where business stakeholders demand a real-time data visualization feature, but the data engineering team states the upstream source pipelines cannot support it? How do you negotiate and document the final solution blueprint