Job description

We are seeking an Enterprise Data Architect to guide the design, development, and governance of enterprise data architectures across complex mission environments. This role combines hands-on architectural expertise with team leadership, oversight of data modeling and integration patterns, and cross-functional coordination with engineering, analytics, AI, and product teams. The Data Architecture Team Lead ensures that data is modeled, structured, governed, and integrated in ways that maximize interoperability, usability, and long-term platform scalability. • Lead a team of Data Architects and Data Engineers in designing conceptual, logical, and physical data models that support analytics, AI/ML, operational applications, and enterprise integration needs. • Develop and maintain canonical data models, semantic layers, metadata structures, and domain-oriented schemas aligned with enterprise data strategies. • Guide the adoption of modern architectural patterns including lakehouse , data mesh, data fabric, domain-driven design, and event-driven integration. • Establish standards for data modeling, schema evolution, semantic consistency, and data contract design across teams and systems. • Partner with Data Engineering, MLOps / LLMOps , and AI Development teams to ensure data architectures support scalable pipelines, feature engineering, and high-performing ML/AI workloads. • Conduct data architecture reviews, ensuring alignment with enterprise reference architectures, security principles, performance expectations, and modernization roadmaps. • Lead integration strategy across platforms, including API-driven data access, streaming and event frameworks, CDC pipelines, virtualization layers, and metadata-driven automation. • Work with mission stakeholders, product teams, and UX researchers to translate requirements into well-designed data structures that support workflows and decision-making. • Oversee governance-aligned design practices, including lineage, cataloging, data quality frameworks, tagging strategies, and Zero Trust data-access patterns. • Mentor Data Architects and senior Data Engineers, elevating architectural thinking, modeling capabilities, and technical decision-making across the team. • Evaluate emerging technologies—metadata platforms, data modeling tools, data virtualization engines, event brokers—and guide strategic adoption. • Contribute to reusable architectural artifacts including reference models, standards, playbooks, integration patterns, and platform design templates. • Support pre-sales and proposal efforts by defining solution architectures, estimating delivery complexity, and articulating modernization strategies. • You will contribute to the growth of our AI & Data Exploitation Practice! • Ability to hold a position of public trust or higher clearance as required . • Bachelor’s or Master’s degree in Computer Science , Data Engineering, Information Systems, Data Architecture, or a related technical field. • 8 + years of experience in data architecture, data engineering, or enterprise information architecture roles. • Strong experience designing conceptual, logical, and physical data models for analytical, transactional, or domain-driven applications. • Proficiency with modern data platforms and architectural patterns including lakehouse , data warehouse, data mesh, streaming architectures, and multi-cloud ecosystems (AWS, Azure, GCP). • Hands-on experience with modeling and metadata tools (e.g., ERWin , ER/Studio, dbt , Collibra, Alation, Atlan, or similar). • Understanding of distributed computing frameworks (Spark, Databricks), relational/NoSQL databases, and cloud-native storage/compute layers. • Experience designing data integration approaches such as ETL/ELT pipelines, streaming (Kafka/Kinesis/EventHub), CDC, API integration, and virtualization. • Knowledge of data governance, metadata management, lineage, data quality, and Zero Trust architecture principles. • Ability to guide cross-functional teams, facilitate design sessions, and influence architectural decisions across programs. • Strong communication skills, capable of translating architectural concepts for technical and non-technical stakeholders, including executive audiences. • Mentoring experience and a demonstrated ability to guide the growth of junior and mid-level architects/engineers. • Preferred certifications: • • CompTIA Network+ • AWS Solutions Architect – Associate or Professional • Azure Data Engineer or Solutions Architect certifications • Google Professional Data Engineer • Databricks Data Engineer Professional • TOGAF, DAMA CDMP, or enterprise architecture certifications Steampunk relies on several factors to determine salary, including but not limited to geographic location, contractual requirements, education, knowledge, skills, competencies, and experience. The projected compensation range for this position is $135,000 to $165,000. The estimate displayed represents a typical annual salary range for this position. Annual salary is just one aspect of Steampunk’s total compensation package for employees. Learn more about additional Steampunk benefits here. Identity Statement As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud. Steampunk is a Change Agent in the Federal contracting industry, bringing new thinking to clients in the Homeland, Federal Civilian, Health and DoD sectors. Through our Human-Centered delivery methodology , we are fundamentally changing the expectations our Federal clients have for true shared accountability in solving their toughest mission challenges. If you want to learn more about our story, visit steampunk.com . We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. Steampunk participates in the E-Verify program. We can recommend jobs specifically for you! Click here to get started.

Requirements

Must-haves

Lead a team of Data Architects and Data Engineers in designing conceptual, logical, and physical data models that support analytics, AI/ML, operational applications, and enterprise integration needs.
Develop and maintain canonical data models, semantic layers, metadata structures, and domain-oriented schemas aligned with enterprise data strategies.
Guide the adoption of modern architectural patterns including lakehouse , data mesh, data fabric, domain-driven design, and event-driven integration.
Establish standards for data modeling, schema evolution, semantic consistency, and data contract design across teams and systems.
Partner with Data Engineering, MLOps / LLMOps , and AI Development teams to ensure data architectures support scalable pipelines, feature engineering, and high-performing ML/AI workloads.
Conduct data architecture reviews, ensuring alignment with enterprise reference architectures, security principles, performance expectations, and modernization roadmaps.
Lead integration strategy across platforms, including API-driven data access, streaming and event frameworks, CDC pipelines, virtualization layers, and metadata-driven automation.
Work with mission stakeholders, product teams, and UX researchers to translate requirements into well-designed data structures that support workflows and decision-making.
Oversee governance-aligned design practices, including lineage, cataloging, data quality frameworks, tagging strategies, and Zero Trust data-access patterns.
Mentor Data Architects and senior Data Engineers, elevating architectural thinking, modeling capabilities, and technical decision-making across the team.
Evaluate emerging technologies—metadata platforms, data modeling tools, data virtualization engines, event brokers—and guide strategic adoption.
Contribute to reusable architectural artifacts including reference models, standards, playbooks, integration patterns, and platform design templates.
Support pre-sales and proposal efforts by defining solution architectures, estimating delivery complexity, and articulating modernization strategies.
You will contribute to the growth of our AI & Data Exploitation Practice!
Ability to hold a position of public trust or higher clearance as required .
Bachelor’s or Master’s degree in Computer Science , Data Engineering, Information Systems, Data Architecture, or a related technical field.
8 + years of experience in data architecture, data engineering, or enterprise information architecture roles.
Strong experience designing conceptual, logical, and physical data models for analytical, transactional, or domain-driven applications.
Proficiency with modern data platforms and architectural patterns including lakehouse , data warehouse, data mesh, streaming architectures, and multi-cloud ecosystems (AWS, Azure, GCP).
Hands-on experience with modeling and metadata tools (e.g., ERWin , ER/Studio, dbt , Collibra, Alation, Atlan, or similar).
Understanding of distributed computing frameworks (Spark, Databricks), relational/NoSQL databases, and cloud-native storage/compute layers.
Experience designing data integration approaches such as ETL/ELT pipelines, streaming (Kafka/Kinesis/EventHub), CDC, API integration, and virtualization.
Knowledge of data governance, metadata management, lineage, data quality, and Zero Trust architecture principles.
Ability to guide cross-functional teams, facilitate design sessions, and influence architectural decisions across programs.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlapiawsazuregcp

Platform: icims
Effort: medium