Senior Data Platform Architect

Clark Construction Group, LLCMcLean, VA
1dOnsite

About The Position

We are seeking a Senior Data Platform Architect to serve as a lead architect and guardian of our enterprise data infrastructure. This is a newly created, high-impact role aimed at bringing the architecture and management of our data platforms in-house, reporting directly to Clark’s Enterprise Data and Analytics lead. In this role, you will be a primary authority over our data ecosystems and platforms. You will move beyond simply "managing platforms" to architecting a Unified Data Foundation through a combination of leading platforms like Snowflake, Databricks, AWS, Microsoft OneLake, and Microsoft Fabric. This foundation serves as the central engine that harmonizes data from across our business (Financial data, IoT and construction processes) to power our next generation of AI and analytics needs for 5000+ users. This is an onsite role in our McLean, VA office.

Requirements

  • 7–10+ years in data engineering, enterprise integration, or platform architecture.
  • Hands-on experience working in a hybrid environment that leverages Snowflake or Databricks for its powerful cloud data warehousing, AWS Infrastructure, Microsoft Fabric (OneLake) for unified data mesh capabilities, and Talend, Matillion, Mulesoft (or similar ETL/ELT tools) for complex enterprise integration.
  • You are equally comfortable discussing API integration patterns as you are writing complex scripts ( eg - python, lambda functions andSQL).
  • You enjoy the "plumbing" and architecture more than the dashboarding.
  • Deep, hands-on expertise in Data Lakehouse technologies like Snowflake, Databricks and ELT/ETL technologies such as Mulesoft, Talend, Matillion, Informatica Cloud services is essential. You should be able to lead an upgrade or migration independently.
  • You have a proven track record of solving scaled problems and building platforms that support 1,000+ users.

Nice To Haves

  • Demonstrated experience in supporting the adoption of AI/ML or other emerging capabilities.
  • Expertise in Business Intelligence (BI) tools such as Tableau, Microsoft Power BI, or Looker.
  • Experience architecting, implementing, and managing highly scalable cloud-based platforms (e.g., Azure Synapse/Fabric, AWS Redshift/S3/PostGres, Google Cloud BigQuery/Storage)
  • AWS Certified Cloud Practitioner: Validated foundational knowledge of AWS Cloud infrastructure, security, and compliance, with a strong grasp of core services including Amazon EC2, S3, RDS, and Lambda to support business-driven cloud initiatives.
  • Experience in a Project-Based Industry (i.e. Construction, Engineering, or Consulting) is a plus, but not required.

Responsibilities

  • Technical Leadership: Serve as the senior technical lead for the platform, establishing the standards for how the platform is architected, managed, data is moved, stored, and secured.
  • Foundational Data Modeling: Design the "Unified Core" of our data creating the logic and common connectors that allow data from various sources to be combined into a single, reliable source of truth for enterprise usage.
  • Complex Data Integration: Architect and maintain mission-critical data flows between disparate enterprise systems, and democratize data consumption to enable self-serve analytics
  • Cross-platform Governance: Implement cross-platform governance and security, ensuring seamless data movement and "Zero-Copy" sharing across data storage and Data Lakehouse - For example - Connectivity between Snowflake Iceberg tables and Microsoft OneLake, integration of SAP Business Data Cloud with Snowflake and Databricks
  • Platform Modernization: You will develop and maintain long-term roadmaps and drive healthy operating stats for data platforms for security, performance and availability. Advise and execute on continuous innovation that will include feature augmentation and selection of new technologies.
  • Data Governance and Catalog: Establish and scale corporate data catalog, ensuring 100% metadata coverage and establishing clear data stewardship roles to improve enterprise data discoverability and trust.
  • System Stability & Scalability: Lead high-priority infrastructure initiatives and upgrades, such as Snowflake upgrades and performance tuning to ensure a resilient, 24/7 production environment.
  • Collaboration: Partner with business ensure the underlying data architecture perfectly supports advanced visualization and machine learning deployments.
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