Job Opportunities API

About CertifyOS CertifyOS is building the data infrastructure that powers modern healthcare. Today, healthcare organizations rely on fragmented and outdated provider data. This creates unnecessary administrative work, regulatory risk, and higher costs across the system. We’re solving that problem. Our API-first platform automates provider licensing, enrollment, credentialing, and network monitoring by connecting directly to hundreds of primary data sources. We help healthcare organizations maintain accurate, compliant, and reliable provider networks at scale. Our vision is simple: One API. One provider ID. Frictionless provider data. We’re backed by leading investors and built by a team with deep experience in provider data systems. At CertifyOS, we value authenticity, accountability, collaboration, results, and openness to feedback. We’re building a high-ownership team focused on solving real infrastructure problems that impact millions of patients. About the Role: We are looking for an Engineering Manager – Data Engineering to lead and scale our data engineering team. This role will be responsible for building reliable, scalable, and high-quality data platforms, pipelines, and analytics infrastructure that power business intelligence, product insights, operational workflows, and customer-facing data capabilities. You will manage a team of data engineers, partner closely with product, analytics, engineering, security, and business stakeholders, and drive the technical roadmap for our data platform. Our data stack is built primarily on Google Cloud Platform, so hands-on experience with the GCP ecosystem is important. Key Responsibilities: Team Leadership - Lead, mentor, and grow a team of data engineers. - Own hiring, onboarding, performance management, career development, and team planning. - Establish strong engineering practices around code quality, documentation, reviews, testing, observability, and incident response. - Create a culture of ownership, accountability, collaboration, and continuous improvement. Data Platform & Architecture - Define and drive the roadmap for scalable data infrastructure on GCP. - Architect and oversee data pipelines, data models, data warehouses, and lakehouse patterns. - Ensure data systems are reliable, secure, cost-efficient, and easy to maintain. - Drive best practices around batch and streaming data processing, orchestration, monitoring, lineage, and data quality. Delivery & Execution - Partner with product, analytics, operations, finance, and engineering teams to understand data needs and deliver high-impact solutions. - Translate business and product requirements into technical plans and execution roadmaps. - Manage project execution, sprint planning, prioritization, and delivery timelines. - Balance short-term business needs with long-term platform investments. Data Governance, Quality & Reliability - Own data quality standards, SLAs, observability, and operational excellence for critical pipelines. - Implement governance practices around data access, privacy, compliance, lineage, and retention. - Ensure the team builds secure and compliant data systems, especially for sensitive or regulated data. Cross-Functional Collaboration - Work closely with analytics, product engineering, infrastructure, security, and leadership teams. - Communicate technical tradeoffs, risks, and roadmap decisions clearly to technical and non-technical stakeholders. - Help define company-wide data standards, tooling, and operating models. Required Qualifications: - 10+ years of experience in software engineering, data engineering, analytics engineering, or platform engineering. - 2+ years of experience managing or leading engineering teams. - Strong hands-on background in building scalable data platforms and pipelines. - Experience with Google Cloud Platform, especially tools such as: - BigQuery - Cloud Storage - Dataf