Data Infrastructure Architect

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Infrastructure Architect based in United States.

This role is responsible for defining and leading the architecture of enterprise-scale data platforms that enable reliable, scalable, and secure data operations. The position focuses on designing modern data ecosystems across ingestion, storage, processing, governance, and analytics layers. You will work closely with engineering, analytics, machine learning, and business teams to create a unified data foundation that supports innovation and strategic decision-making. The ideal candidate brings deep expertise in modern data architectures, strong technical leadership, and experience delivering complex platform initiatives. This opportunity offers the chance to influence enterprise data strategy, establish best practices, and shape the future of data-driven solutions. Working remotely, you will contribute to impactful technology initiatives while collaborating with cross-functional teams across the organization.

The Data Infrastructure Architect will define the technical vision and architecture strategy for enterprise data platforms, ensuring scalability, reliability, governance, and performance. This role requires strong architectural expertise, hands-on technical understanding, and the ability to guide teams through complex data initiatives.

Define and lead the architecture of enterprise data platforms across ingestion, storage, processing, governance, and consumption layers.

Establish data architecture standards, patterns, and best practices to support scalable and maintainable solutions.

Design and evolve modern data platform architectures, including lakehouse environments, streaming systems, and cloud-based data solutions.

Partner with data engineering, analytics, machine learning, and business teams to deliver a cohesive and effective data foundation.

Guide the selection, implementation, and optimization of enterprise data technologies and platforms.

Develop and maintain data modeling strategies across dimensional, normalized, and data-vault approaches.

Drive implementation of data governance frameworks, including lineage, cataloging, security, and lifecycle management.

Provide architectural guidance for data processing solutions using technologies such as Spark, Flink, and Kafka.

Support cloud architecture decisions involving infrastructure, networking, identity management, security, and cost optimization.

Lead large-scale data platform initiatives across multiple teams, ensuring alignment with business objectives and technical standards.

Communicate complex architectural concepts clearly to technical and non-technical stakeholders.

Requirements:

The ideal candidate has extensive experience designing and delivering enterprise data platforms, with strong knowledge of modern data architecture patterns and cloud technologies. They should combine technical depth with strategic thinking, leadership capabilities, and strong communication skills.

Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related technical field.

8+ years of experience in data engineering, including significant experience in architecture-focused roles.

Deep expertise with major data platforms such as Snowflake, Databricks, BigQuery, or Redshift.

Strong understanding of lakehouse architectures, modern table formats, and large-scale streaming systems.

Hands-on production experience with technologies such as Spark, Flink, or Kafka.

Strong expertise in data modeling methodologies, including dimensional, normalized, and data-vault approaches.

Experience implementing data governance, lineage, metadata management, and catalog capabilities.

Solid understanding of cloud platforms, networking concepts, identity management, and cost optimization strategies.

Proven experience leading complex data platform programs across multiple teams and stakeholders.

Excellent communication, facilitation, and stakeholder management skills.

Experience with data mesh or data product architectures is preferred.

Familiarity with semantic layer technologies such as dbt Semantic Layer, Cube, or LookML is a plus.

Experience working in regulated environments with strict compliance, audit, or data residency requirements is preferred.

Cloud or data platform certifications across Snowflake, Databricks, AWS, Azure, or GCP are advantageous.

Experience contributing to technical publications, presentations, or industry discussions is a plus.

Benefits:

Competitive annual salary range of $175,000 - $200,000 USD .

Fully remote work opportunity available across the United States.

Full-time direct employment opportunity.

Opportunity to work on enterprise-scale data architecture initiatives with significant technical impact.

Career growth opportunities within a technology-focused environment.

Exposure to modern cloud, AI, analytics, and enterprise data solutions.

Collaborative work culture with cross-functional teams and challenging technical projects.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1