Engineering Manager - Data Engineering

CertifyOS

18h

About The Position

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 Today, healthcare organizations rely on fragmented and outdated provider data.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.

Requirements

• 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, Dataflow, Dataproc, Pub/Sub, Cloud Composer / Airflow, Cloud Functions or Cloud Run
• Strong experience with SQL and at least one programming language such as Python, Java, or Scala.
• Experience with data modeling, ETL/ELT pipelines, workflow orchestration, and data warehouse design.
• Strong understanding of data quality, monitoring, lineage, and governance practices.
• Experience operating production data systems with SLAs and incident management.
• Strong communication skills with the ability to influence across engineering, product, analytics, and business teams.

Nice To Haves

• Experience with healthcare, fintech, SaaS, or other regulated data environments.
• Experience with HIPAA, SOC 2, GDPR, or similar compliance frameworks.
• Experience with dbt, Looker, Fivetran, Airbyte, Terraform, Kubernetes, or Docker.
• Experience with real-time streaming architectures.
• Experience managing cloud cost optimization for data workloads.
• Experience building self-serve data platforms for analytics and business users.
• Experience with master data management, data contracts, or data mesh principles.

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.

Benefits

• 100% coverage of health, dental, and vision insurance premiums for employees.
• Unlimited PTO, with at least two weeks off each year to recharge (for US-based team).
• Health insurance, statutory leave benefits, and additional wellness (menstrual) leave for women (for India employees).
• Pay transparency and an open culture where compensation conversations are encouraged and respected.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed