Data Architect

Must be a US Citizen or GC

We are seeking a hands-on, highly technical Data Architect to lead the end-to-end design and technical architecture of our enterprise Data Lakehouse environment. Operating in a flexible hybrid model (3 days in-office / 2 days remote).


In this high-impact position, you will partner closely with the Database Platform Lead, downstream developers, and business stakeholders to translate complex business needs into scalable, secure, and robust data solutions. Serving as the primary technical authority for our Data Lakehouse, you will design data models, pipelines, and integrations that power advanced business intelligence, operational reporting, analytics, and firm-wide AI initiatives. If you are a collaborative problem-solver who excels at bridging high-level architecture with deep, hands-on implementation, we want to hear from you.

### Key Responsibilities

- Architect the Enterprise Lakehouse: Own and maintain the technical architecture of the organizations Data Lakehouse, ensuring scalable, high-performing, and secure environments aligned with enterprise standards.
- Data Modeling & Integration Design: Design robust data structures, relational and dimensional models, data flows, and ELT/ETL pipelines to integrate data from diverse enterprise applications, databases, and APIs.
- Collaborate with Cross-Functional Teams: Work hand-in-hand with the Database Platform Lead, BI Developers, AI Solutions Engineers, and software developers to build downstream-ready data assets and resolve complex data dependencies.
- Technical Leadership & Implementation: Provide hands-on guidance throughout the development lifecycle, establishing best practices for data transformation, pipeline orchestration, data validation, and performance tuning.
- Governance & Quality Standards: Define and enforce standards for data governance, metadata management, lineage, data security, and access controls within the data ecosystem.
- Evaluate Emerging Tech & Drive Innovation: Assess next-generation cloud data tools, automation frameworks, and AI-driven platforms (such as Microsoft Fabric and Databricks innovations) to continuously enhance firm capabilities.
- Comprehensive Documentation: Produce detailed architectural blueprints, data dictionaries, mapping specifications, and integration workflows to support the data ecosystem across its lifecycle.

### Required Skills and Qualifications

- Education & Experience: Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field (or equivalent experience), plus a minimum of 5 years of proven experience in data architecture, data engineering, or enterprise data warehousing.
- Cloud Lakehouse Expertise: Demonstrated hands-on experience designing and building enterprise data architectures utilizing Microsoft Azure and Databricks .
- Advanced SQL & Modeling: Strong proficiency in SQL with deep expertise in dimensional modeling, data lake/lakehouse storage patterns, relational structures, and schema design.
- ETL/ELT & Pipeline Engineering: Proven track record designing end-to-end data pipelines, data ingestion workflows, connector configurations, and API integrations.
- Analytical & Communication Skills: Exceptional problem-solving skills with the ability to translate strategic business requirements into technical execution and communicate complex concepts to diverse audiences.
- Preferred Qualifications:
- Experience with Python, PySpark, Microsoft Fabric, Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), and Power BI.
- Familiarity with CI/CD tools (Azure DevOps/Git) and enterprise orchestration tools.
- Prior experience in legal tech, professional services, or confidentiality-sensitive environments.
- Relevant Azure or Databricks certifications.