Bachelor's degree in Computer Science, Information Technology, or related field.
10+ years of professional data engineering experience.
10+ years in an enterprise Data Architect role focusing on architecture strategy and standards.
5+ years of experience with Snowflake, Azure Data Factory, Azure Synapse, and SQL Server.
Strong data governance experience involving metadata management and regulatory compliance.
Responsibilities
Define and govern the enterprise data architecture vision and standards.
Design scalable and secure enterprise data platforms using modern technologies.
Establish solution patterns for various data pipeline types to support analytics.
Lead data modeling strategies to enhance consistency and performance.
Set architecture standards for data quality, security, and access controls.
Provide technical guidance to Data Engineering teams for modernization and optimization.
Communicate architecture direction and standards to stakeholders.
Benefits
Hybrid work environment.
Excellent medical, dental, and vision insurance.
Life insurance and disability insurance options.
Parental Leave Policy.
401K with company match.
Generous PTO plan and paid holidays.
Full Job Description
GAINSCO is seeking an Enterprise Data Architect to define and govern our enterprise-wide data and analytics architecture strategy. As a recognized subject matter expert, you will establish the long-term vision, standards, reference models, and architectural patterns that guide how data is ingested, integrated, stored, modeled, governed, and delivered across the organization. You will partner with business leaders, Data Engineering, Analytics, Security, and Governance teams to design and implement scalable, secure, and reusable data solutions. This role will guide modernization, shape enterprise data products, and present new or revised architecture standards to senior leadership to support a more optimized, secure, and stable data environment.
What does an Enterprise Data Architect do?
Define and govern the enterprise data architecture vision, principles, roadmaps, reference models, and design standards.
Design scalable, secure, and resilient enterprise data platforms using Snowflake, Azure Data Factory, Azure Data Lake, Azure Synapse, SQL Server, Kafka, and cloud-agnostic technologies.
Establish solution patterns for batch, streaming, real-time, and event-driven data pipelines that support analytics and operational use cases.
Lead conceptual, logical, and physical data modeling strategies to strengthen consistency, performance, and reuse.
Set architecture and governance standards for metadata, lineage, data quality, security, access controls, semantic models, enterprise datasets, and self-service analytics.
Provide design reviews and technical guidance to Data Engineering teams while driving modernization, platform optimization, cost efficiency, and reduction of technical debt.
Communicate architecture direction, standards, and technical trade-offs to senior leaders, engineers, analysts, and business stakeholders.
Mentor junior architects and engineers while promoting consistent architecture practices across the organization..
What is required?
Education:
Bachelor's degree in Computer Science, Information Technology, or a related field required.
Experience:
10+ years of professional data engineering experience.
10+ years of experience in an enterprise Data Architect role, with responsibility for architecture strategy, standards, reference models, design patterns, or technical roadmaps.
5+ years of experience with Snowflake, Azure Data Factory, Azure Synapse, and SQL Server.
5+ years of experience with streaming, replication, or event-driven data technologies, such as Kafka, Openflow, Snowpipe, or comparable platforms.
5+ years of experience with Power BI and Tableau, including enterprise reporting architecture, semantic modeling, dataset design, dashboard governance, or analytics enablement.
Strong experience designing secure, scalable, reliable, and cost-efficient cloud data platforms.
Strong data governance experience involving metadata management, lineage, data quality, security, access controls, and regulatory compliance.
Experience applying DevOps methodologies, CI/CD workflows, ITIL practices, and Git-based development within enterprise data environments.
Experience communicating architecture standards, recommendations, and technical trade-offs to senior leadership and technical teams.
Other skills and abilities:
Familiarity with Terraform or other infrastructure-as-code tools.
Knowledge of containerization and orchestration technologies, including Docker and Kubernetes.
Exposure to data science workflows, machine learning platforms, or ML model integration.
Strategic and systems-level thinking with the ability to connect business priorities to enterprise data architecture.
Strong knowledge of modern data architecture, cloud platforms, data integration, modeling, analytics, and reporting.
Ability to design and implement solution patterns and reusable data products across enterprise environments.
Strong architecture review, technical decision-making, and problem-solving capabilities.
Ability to evaluate emerging technologies based on business value, risk, scalability, security, and cost.
Strong communication and presentation skills, including the ability to explain complex architecture concepts to non-technical stakeholders.
Ability to influence decisions, establish alignment, and lead cross-functional teams without direct authority.
Ability to mentor junior architects and engineers and strengthen architecture practices across teams.
What else do you need to know?
Hybrid
Excellent benefits package medical & dental, vision insurance, life insurance, short-term and long-term disability insurance.
