Data Architect

T-Rex Solutions is seeking a qualified Data Architect to support the 2028 Census Test program, an end-to-end dry run of the operations in preparation for the 2030 Decennial Census. During the test both the enterprise processes and data systems will be verified and fine-tuned to ensure the success of the large-scale national survey. Specifically relevant to this position, the solution will be a data-centric system with a data lake using Redshift on AWS at its core.

This solution is expected to transform the processing within the system from what was historically a batch processing system to a more incremental one that processes individual responses as they are collected. Additionally, the Census Bureau intends to increase the usage of Administrative Data during this processing.  As such, the data structures used within this data lake must be efficiently defined to maximize the flexibility for the potential use and addition of administrative data as well as facilitate incremental and large-scale statistical processing.

Responsibilities:

Hands-on design of the data architecture to be used within the Census Enterprise Data Lake for 2030 Census processing. This structure will compose data from 350+ million person records, 18-+ million address records, and other associated administrative data.

Perform analysis on data workflow and detail requirements to map them into big data artifacts in Cloud environment

Review the high-level design of the entire decennial data architecture across 50+ different enterprise systems

Produce data architecture artifacts such as decennial-wise conceptual, logical, and lineage data models for both management and technical users

Work with system owners to identify key data entities and relationships on the basis of business context

Build data architecture prototypes to demonstrate the effectiveness and efficiency of the big data design approach

Review Census data sets and conduct empirical studies as needed to build an optimal data infrastructure to support the mission

Identify the complex relationships within various data sets and define corresponding data objects for incremental processing

Frequently coordinate and collaborate with the various system teams and other contractors that will populate and use data via these structures to efficiently build the structures to facilitate their update, maintenance, ability to search, and ability to compare to administrative data for QA and other purposes.

Frequently coordinate and collaborate with the various statistical organizations that will analyze this data to efficiently build the structures to facilitate this analysis.

Coordination with the Census Bureau data architect to drive alignment with the Enterprise Master Data  in a highly visible position to work with client team closely to understand the business needs and identify the key solution areas.

Provides technical/management leadership on major tasks or technology assignments. Establishes goals and plans that meet project objectives.

Develop roadmaps and provide technical strategy directions for the development and delivery of a new enterprise data framework.

Transform business requirements into data driven solutions including architectural design, component standardization, technical process flow, and cost-effective implementation approaches.

Participate as needed in all aspects of software development with emphasis on the planning, analysis, design, integration, and presentation.

Apply principles, design methods and data architecture knowledge to specific requirements in the context of a complex, large-scale enterprise data framework.

Coordinate with senior management on project activities including business analysis, client collaboration, product provisions, and project staffing.

Provide high-level support for system design, development, integration, and coordination.

Requirements:7+ years of experience developing data architecture and data engineering solutions at enterprise scale

Bachelor’s degree in Computer Science or related field

Expertise in using Amazon Web Services (AWS) environment and/or other Cloud environments

Expertise in using data warehouses such as Redshift, Snowflake, or similar technologies

Expertise in a wide range of cloud data services and data structures  (in addition to data warehouse), such as data lake, Iceberg table, document DB, key-value DB, and time-series DBStrong general data engineering knowledge, including data transformation, data loading, data procedure writing, and data…