Job Description

IT Architect (Airport Data Architect)

Salary Range: $96,945 - $161,647

Posting Expires: March 10, 2025

General Description and Classification Standards:

The Data Architect will focus on developing and optimizing pipelines to ingest, process, and manage data for the Department of Aviation's (DOA) data ecosystem. This role is critical in enabling Data BI Engineers and Data Scientists to access clean, structured, and scalable datasets for analytics, reporting, and advanced modeling.
The architect will work closely with data stewards across DOA business units (e.g., Marketing, Concessions, Finance) and collaborate with IT teams (infrastructure, network, security, development) to design and implement solutions that align with organizational goals and hybrid cloud platforms. Key responsibilities include researching, presenting, and delivering scalable data architecture strategies to ensure efficient data flow and integration.

Essential Duties and Responsibilities:

These are typical responsibilities for this position and should not be construed as exclusive or all inclusive.

Designs, develops, and maintains scalable pipelines to ingest and process data into the data lake. Collaborates with stakeholders to define data architecture strategies, best practices, and standards. Ensures data availability, quality, and consistency to support Data BI Engineers, Data Scientists, and other analytical teams. Conducts advanced data modeling, predictive analytics, and machine learning techniques to derive actionable insights and improve operations. Analyzes, manipulates, and processes large datasets using statistical and analytical tools. Designs, validates, and optimizes data models to forecast trends and improve decision-making processes. Creates visualizations such as graphs, charts, and dashboards to communicate analytical results effectively to stakeholders. Strategizes and identifies innovative approaches to source, collects, and explores data from various sources, ensuring maximum value extraction. Maintains comprehensive data documentation, including schema designs, mapping documents, data flow diagrams, architecture documentation, and reporting outputs. Researches and implements modern data warehousing techniques, including hybrid cloud solutions, to support evolving business needs. Identifies and recommends innovative uses for existing data sources while designing and building new data processes and large-scale datasets. Stays current with emerging technologies, industry best practices, and trends in data architecture, data science, and analytics to enhance the organization's capabilities. Ensures compliance with established data standards, governance principles, metrics, and architecture guidelines. Recommends data-driven solutions and strategies to senior leadership based on insights derived from data analysis. Supports organizational goals by solving business problems, including budgeting, staffing, and strategic decision-making, through data-driven analysis. Drives continuous improvement in data capabilities by researching and adopting cutting-edge techniques and tools. Perform additional duties as assigned.


The above statements reflect the general duties, responsibilities and competencies considered necessary to perform the essential duties and responsibilities of the job and should not be considered as a detailed description of all the work requirements of the position. COA may change the specific job duties with or without prior notice based on the needs of the organization.

Knowledge Skills and Abilities:

This is a partial listing of necessary knowledge, skills, and abilities required to perform the job successfully, it is not an exhaustive list.

Technical Expertise:

Proficiency in designing and managing data pipelines using modern tools and frameworks (e.g., Apache Spark, Azure Data Factory, AWS Glue). Strong understanding of data lake architectures and data warehouse solutions. Familiarity with hybrid cloud platforms and data governance policies.

Collaboration and Communication:

Proven ability to work effectively with cross-functional teams, including business units and IT departments. Excellent written and verbal communication skills to present technical concepts to diverse audiences.

Problem Solving and Innovation:

Ability to troubleshoot and optimize data pipelines for performance and scalability. * A passion for innovation and staying updated with industry trends in data engineering and architecture.