What are the responsibilities and job description for the Senior Data Architect & Reporting Solutions D position at Datavault AI Inc.?
Employment Type: Full‑Time, Remote
About Us
Datavault AI, along with its event-technology subsidiary Event Citadel (formerly CompuSystems), operates across a diverse portfolio of technology and service divisions.
Datavault AI Inc. delivers high-performance computing software, Web 3.0 data-management solutions, and advanced audio technologies to a broad range of industries. Its Acoustic Science division licenses spatial and multichannel HD audio technologies—including ADIO®, WiSA®, and Sumerian®—to customers in sports & entertainment, events & venues, automotive, finance, and other sectors.
Event Citadel (formerly CompuSystems), founded in 1976, is a trusted provider of end-to-end event technology solutions, offering registration, ticketing, lead retrieval, and attendee-engagement services for events of all sizes across trade, association, corporate, and government markets.
Job Description
We are seeking a Senior Data Architect & Reporting Solutions Designer to define and build the next‑generation data foundation that powers enterprise analytics, operational reporting, and strategic decision‑making. This role blends deep expertise in data architecture, production‑grade ETL/ELT engineering, and reporting design, ensuring that data is modeled, transformed, and delivered with reliability, clarity, and scale. You will architect end‑to‑end data ecosystems—from ingestion pipelines to semantic layers—while shaping how data is presented through enterprise reporting platforms.
Responsibilities
Data Architecture & Modeling
- Architect scalable, secure, and high‑performance data environments across cloud and on‑prem systems.
- Design logical and physical data models for operational reporting, analytics, and executive dashboards.
- Build semantic layers, dimensional models, and data marts optimized for BI consumption.
- Define data standards, modeling conventions, and architectural patterns that ensure long‑term maintainability.
Production‑Grade ETL/ELT Engineering
- Design and implement automated, resilient, and low‑maintenance ETL/ELT pipelines for batch and streaming data.
- Build ingestion and transformation workflows using tools such as Airflow, dbt, Spark, Kafka, or similar frameworks.
- Implement robust data‑quality checks, schema evolution strategies, and lineage tracking.
- Optimize pipelines for performance, cost efficiency, and operational reliability.
Reporting Architecture & Data Presentation
- Shape data structures specifically for reporting, dashboarding, and self‑service analytics.
- Partner with business stakeholders to translate reporting needs into scalable data models and curated datasets.
- Define KPI frameworks, metric definitions, and standardized reporting logic across the organization.
- Ensure data is presented in a way that is intuitive, consistent, and aligned with business objectives.
Enterprise Reporting Integration
- Integrate and manage enterprise‑grade BI platforms (Power BI, Tableau, Looker, Qlik, MicroStrategy, etc.).
- Architect secure, performant data connections, refresh strategies, and semantic models.
- Collaborate with analysts and business teams to design dashboards, reports, and analytic workflows.
- Implement governance around report lifecycle management, versioning, and access control.
Data Governance, Security & Compliance
- Define and enforce data governance frameworks including cataloging, lineage, retention, and stewardship.
- Implement privacy‑by‑design principles and ensure compliance with regulatory requirements.
- Architect secure data‑exchange mechanisms using encryption, tokenization, and role‑based access controls.
Technical Leadership
- Provide architectural guidance to data engineering, analytics, and reporting teams.
- Evaluate emerging technologies in data modeling, ETL automation, BI tooling, and metadata management.
- Produce architecture diagrams, data flow documentation, and technical specifications.
- Champion best practices for data quality, modeling, and reporting across the organization.
Qualifications
- 5 years in data architecture, data engineering, or enterprise reporting design.
- Strong expertise in:
- Data modeling (relational, dimensional, semantic)
- SQL and NoSQL systems
- ETL/ELT pipeline design
- Cloud data platforms (AWS, Azure, or GCP)
- Hands‑on experience with:
- Data warehouses (Snowflake, Redshift, BigQuery)
- Orchestration frameworks (Airflow, Dagster, dbt)
- Streaming systems (Kafka, Kinesis, Pub/Sub)
- Enterprise BI tools (Power BI, Tableau, Looker, etc.)
- Deep understanding of data governance, security, and compliance frameworks.
- Ability to translate business requirements into scalable data and reporting architectures.
Preferred
- Experience designing semantic layers and enterprise reporting models.
- Background in high‑volume data environments or event‑driven architectures.
- Familiarity with metadata management, data catalogs, and lineage tools.
- Experience supporting finance, marketing, operations, or product analytics teams.
What We Offer
- Competitive compensation and benefits.
- Influence over the architectural direction of a modern enterprise data platform.
- Opportunities to work with advanced data modeling, ETL automation, and BI technologies.
- A culture that values technical rigor, ownership, and innovation.