Data Platform Architect

Job Description

• This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Platform Architect in the United States. This role is a senior-level architecture position responsible for defining and shaping the foundation of a modern enterprise data platform. You will lead the design of scalable, secure, and high-performance data ecosystems spanning ingestion, storage, processing, and consumption layers. The position requires deep technical expertise in cloud data platforms, streaming systems, and lakehouse architectures, along with strong architectural leadership across cross-functional teams. You will collaborate closely with data engineering, analytics, ML, and business stakeholders to ensure data is structured, governed, and accessible for advanced use cases. A key part of the role involves setting enterprise-wide standards for data modeling, governance, and lifecycle management. This is a highly strategic position where your decisions directly influence data reliability, scalability, and business intelligence capabilities at scale.
• Accountabilities: Define and evolve the enterprise data platform architecture across ingestion, storage, processing, and consumption layers. Establish standards for data modeling, schema design, partitioning strategies, and data lifecycle management. Design and optimize modern data architectures including lakehouse, warehouse, and streaming solutions using platforms such as Snowflake, Databricks, BigQuery, Redshift, Iceberg, Delta Lake, or Hudi. Develop end-to-end data pipelines ensuring performance, reliability, scalability, and cost efficiency across batch and streaming systems. Lead implementation of data governance, cataloging, lineage, and metadata management solutions using tools such as Collibra, Alation, Atlan, or DataHub. Define and enforce data security architecture including access controls, encryption, masking, and identity-based governance. Partner with analytics, ML, and business teams to align platform capabilities with downstream data consumption needs. Provide architectural leadership, conduct design reviews, and mentor engineering teams on best practices and standards. Drive cloud cost optimization, capacity planning, and operational excellence across data infrastructure. Design disaster recovery, high availability, and multi-region strategies for enterprise data systems. Requirements: Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field. 8+ years of experience in data engineering with strong focus on data architecture and platform design. Deep expertise in at least two major data platforms (e.g., Snowflake, Databricks, BigQuery, Redshift). Strong hands-on experience with distributed processing and streaming technologies such as Spark, Flink, or Kafka. Solid understanding of lakehouse architecture, modern data formats, and scalable data modeling techniques. Experience implementing data governance, lineage, metadata, and catalog solutions in enterprise environments. Strong knowledge of cloud infrastructure, networking, identity management, and cost optimization strategies. Proven ability to lead large-scale data platform initiatives across multiple teams. Excellent communication, stakeholder management, and architectural documentation skills. Experience with data mesh concepts, semantic layers, or regulated data environments is a plus. Benefits: Competitive compensation aligned with experience and expertise Full-time, direct W2 employment with long-term engagement stability 100% remote work within the United States Comprehensive benefits package including healthcare coverage Opportunity to work on enterprise-scale, modern data platform architecture Exposure to leading cloud and data technologies across multiple domains Strong emphasis on professional growth and technical leadership development Collaborative engineering culture focused on innovation and best practices Inclusive and equal opportunity workplace environment.
• 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
• We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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