Data Architect

About the role

ALTEN Technology delivers engineering solutions for aerospace, medical devices, and autonomous vehicles. This role defines and supports enterprise data strategy within a large global engineering organization.

Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.

Key facts

What you'll do

Enterprise data strategies are defined and supported to align organizational objectives across applications.

The architecture for these integrations is shaped to meet evolving business requirements and technical constraints.

These platforms are enhanced to deliver greater value for enterprise analytics and decision-making.

Solutions are implemented to maintain consistency and reliability across the data landscape.

Data models, architecture decisions, and integration patterns are documented to create a clear, shared understanding. This documentation serves as a reference for current and future data initiatives.

Requirements

Strong experience in data architecture, data management, and enterprise data solutions must be demonstrated for this role.

Design of data flows, application integrations, and functional interfaces between systems has to be shown.

Knowledge of data lakes, centralized repositories, and modern data platforms is essential for success in this position. Familiarity with these technologies is required to perform core responsibilities.

Experience supporting data governance, data quality, and data lifecycle management is a strong advantage in complex environments. This experience helps ensure that data remains reliable, secure, and compliant.

Collaboration with business and technical teams to define scalable data solutions is necessary for this position. Effective partnership is required to align technical approaches with organizational objectives.

A degree is required as a stated qualification for this role. The credential confirms foundational knowledge relevant to the position.

Practical notes

aerospace programs and export-controlled environments. Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

Data architecture work connects business goals with technology capabilities through structured models and standards.

Modern data platforms, data lakes, and repositories support scalable storage and analytics for enterprise needs.

Data governance, data quality, and lifecycle practices help maintain reliable and compliant information management.

Cross-functional collaboration aligns technical designs with business priorities and regulatory requirements.

Clear documentation of decisions and patterns supports consistent implementation and future maintenance.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.