Engineering Manager - Data Engineering

Posted Yesterday
Be an Early Applicant
Hiring Remotely in Pune, Maharashtra, IND
In-Office or Remote
Expert/Leader
Healthtech • Social Impact • Software
Frictionless provider intelligence.
The Role
Lead and grow a data engineering team to build scalable, reliable data platforms and pipelines on GCP. Drive architecture, roadmap, governance, SLAs, observability, and cross-functional delivery to enable analytics, product insights, and customer-facing data capabilities while ensuring security and compliance.
Summary Generated by Built In

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Today, healthcare organizations rely on fragmented and outdated provider data.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

    • 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.

Preferred Qualifications

  • 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.

What Success Looks Like

In this role, you will:

  • Build and lead a high-performing data engineering team.

  • Deliver reliable, scalable, and well-governed data pipelines and platforms.

  • Improve data availability, quality, and trust across the organization.

  • Enable analytics, reporting, product intelligence, and operational workflows through robust data infrastructure.

  • Create clear technical direction and execution discipline for the data engineering function.

Benefits of Working at Certify

At Certify, we’re building with intention and taking care of the people doing the work.

Your well-being matters to us. We provide 100% coverage of health, dental, and vision insurance premiums for employees. Our US-based team benefits from unlimited PTO, with at least two weeks off each year to recharge. In India, employees are supported with health insurance, statutory leave benefits, and additional wellness (menstrual) leave for women.

We are an equal opportunity employer committed to building an inclusive environment where everyone feels valued and empowered to do their best work, and we welcome applicants from all backgrounds and experiences.

If you require reasonable accommodations during the application process, please contact [email protected].

We are also committed to pay transparency and foster an open culture where compensation conversations are encouraged and respected.

Skills Required

  • 10+ years experience in software, data, analytics, or platform engineering
  • 2+ years managing or leading engineering teams
  • Hands-on experience building scalable data platforms and pipelines
  • Experience with Google Cloud Platform (BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Cloud Composer/Airflow, Cloud Functions or Cloud Run)
  • Strong SQL skills and proficiency in at least one language: 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
  • Experience operating production data systems with SLAs and incident management
  • Strong communication and cross-functional influencing skills
  • Experience with healthcare, fintech, SaaS, or other regulated data environments
  • Familiarity 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
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The Company
New York, New York
70 Employees
Year Founded: 2021

What We Do

CertifyOS is a first-of-its-kind provider intelligence platform, powered by API integrations and hundreds of verified data points. We unlock insights and power performance for clinicians, teams and organizations, with frictionless licensing and enrollment, one-click credentialing and real-time network monitoring at your fingertips.

Why Work With Us

We are a remote team-first culture that ensures every employee has the opportunity to grow and learn. Join our team and feel good about what you’re doing and where you’re going.

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