Austin Aviation IT Data Architect

About This Position As an IT Data Architect, you will design, build, and optimize the enterprise data platform that powers reporting, analytics, artificial intelligence, and business decision-making.

You'll develop scalable data pipelines, integrate data from multiple systems, and create modern data architectures such as data warehouses, data lakes, and data hubs. Working closely with business stakeholders, data analysts, engineers, and application teams, you'll ensure data is accurate, secure, accessible, and production-ready.

This role combines technical expertise with strategic thinking, requiring experience in ETL/ELT, SQL, cloud data platforms, data modeling, automation, and modern analytics technologies. Success in this position means transforming complex data into trusted enterprise assets that enable smarter decisions across the organization while following governance, security, and change management best practices.

Job Description:

IT Data Architect

Purpose:

IT Data Architects build and manage the data pipelines necessary to support value creation, growth, and delivery of IT results through designing and implementing the data and analysis infrastructure. This position optimizes data pipelines and moves data pipelines effectively into production for key data and analytics consumers by working across the City and with IT and other subject matter experts to plan and deliver optimal analytics and data solutions to users.

Duties, Functions and Responsibilities:
Essential duties and functions, pursuant to the Americans with Disabilities Act, may include the following. Other related duties may be assigned.

Assists in building and managing the data pipelines necessary to support value creation, growth, and delivery of business and IT results.

Designs and implements the data and analysis infrastructure, including complex databases.

Assists in developing different technical tools/services to enable large scale machine learning solutions.

Works closely with Data Analysts, and others to develop scalable and production ready Advanced Analytics and supporting software.

Assists in building and maintaining data management systems and data pipelines that combine core data sources into data warehouses or other accessible structures to support reporting and analytical systems.

Documents models, solutions, and implementations (e.g., Data Mapping, Technical Specifications, Production Support, Data Dictionaries, Test Cases, etc.).Creates data transformation processes (ETL, SQL stored procedures, etc.) to support moderately complex to complex business systems and operational data flows.

Responsibilities
- Supervisor and/or Leadership Exercised:
May provide leadership, work assignments, evaluation, training, and guidance to others.

Knowledge, Skills, and Abilities:
Must possess required knowledge, skills, abilities, and experience and be able to explain and demonstrate, with or without reasonable accommodations, that the essential functions of the job can be performed.

Knowledge of languages such as (R, Pearl, Python, Java, C++, C#, Scala etc.), modern data storage and access technologies, including caching, application of No

SQL, Key/Value, and RDBMS data stores.

Knowledge of commercial data science platforms (e.g., Python, R, KNIME, Alteryx, etc.).Knowledge of Extract-Transform-Load (ETL) processing and Change Data Capture (CDC) technologies.

Knowledge of big data concepts and frameworks and business intelligence tools (such as Tableau, Qlik, PowerBI) and AI frameworks (Caffe, Tensor Flow)
Knowledge of Data Management architectures like Data Warehouse, Data Lake, Data Hub and the supporting processes like Data Integration, Governance,Metadata Management.

Knowledge of data pipeline guiding principles, and best practices to build and maintain data pipelines.

Skill in data storage, data processing, database fundamentals, data orchestration and automation, programming, CI/CD, data validation and testing, version control systems, scripting and coding, cloud migration, metadata management, infrastructure as a code (IAC), data monitoring and observability skills.

Ability to build, manage and optimize data pipelines that facilitate data movement.

Ability to reduce manual data work and improve productivity.

Ability to build robust data operations and to identify critical issues faster in order to debug and troubleshoot quickly.

Ability to work with and across teams and foster a cooperative and efficient working environment.

Ability to consider and incorporate the…