Lead Data Architect

We are seeking a Principal Data Solution Architect / Lead Data Architect to serve as the senior-most technical authority for end-to-end data architectures, cloud data platforms, integration strategies, and enterprise-scale modernization initiatives.

What You Will Do

Design enterprise data ecosystems, translate mission and business needs into actionable data architecture roadmaps, architect robust ingestion, transformation, and serving layers, lead end-to-end data modeling strategy, and partner with Data Engineering, Data Science, AI/ML Engineering, and LLMOps/MLOps teams.

Why It Might Be a Fit

This role operates at the intersection of architecture, engineering, analytics, AI, and mission strategy. The Principal Data Solution Architect shapes the vision for how data is collected, governed, transformed, stored, accessed, and activated across complex environments—ultimately enabling reliable analytics, ML/AI capabilities, and mission-critical applications.

Requirements

• Ability to hold a position of public trust or higher clearance as required.
• Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Engineering, Information Systems, Cloud Architecture, or a related technical field.
• 10+ years of professional experience designing enterprise-scale data solutions, with significant architectural leadership.
• Expert-level knowledge of modern data architectures including lakehouse, data mesh, data fabric, MDM, event-driven architectures, and domain-driven design.
• Deep experience with cloud-native data ecosystems across AWS, Azure, or GCP—including storage, compute, orchestration, serverless, virtualization, containerization, and security services.
• Mastery of distributed data processing frameworks (e.g., Spark, Databricks, Flink, Kafka, Synapse, Dataflow) and strong proficiency in SQL and Python.
• Proven ability to design end-to-end ingestion pipelines, transformation logic, metadata systems, feature stores, and data serving layers optimized for analytics and AI workloads.
• Understanding of enterprise data governance, including cataloging, lineage, privacy, tagging, Zero Trust access patterns, and compliance requirements.
• Strong communication skills with the ability to influence senior stakeholders, justify architectural decisions, and translate complex concepts into actionable insights.
• Demonstrated success mentoring technical staff, leading architecture reviews, and guiding multi-team delivery across complex modernization programs.
• Experience collaborating with Data Science, AI/ML, and MLOps teams to ensure data architectures support scalable model development and operationalization.

Benefits

• Annual salary is just one aspect of Steampunk’s total compensation package for employees. Learn more about additional Steampunk benefits here.