We are seeking a skilled Mid-Level Data Engineer to join our Data Platform team. At this level, you will be a hands-on executor and domain owner — responsible for building, maintaining, and improving the pipelines and data models that power analytics and business intelligence across the company. You will own specific areas of our BigQuery data warehouse end-to-end, delivering reliable data products within a framework set by senior and staff engineers.

This is not an architecture or strategy role — it is a role for someone who takes well-defined problems and executes them with high craft and reliability. You will work closely with data analysts, analytics engineers, and product teams, and are expected to grow toward greater technical ownership over time.

Key Duties

• • • Build and maintain production-grade ELT pipelines that ingest data from internal applications, third-party SaaS tools, and event streams into our BigQuery data warehouse.
    • Own specific data domains end-to-end — from raw ingestion through to marts — ensuring your areas of the warehouse are accurate, tested, and well-documented.
    • Write and maintain dbt models, tests, macros, and documentation within our established dbt project conventions and code review process.
    • Develop and manage Airflow DAGs on Cloud Composer or other similar tools to orchestrate data workflows, following patterns and standards set by the team.
    • Implement data quality checks and monitoring to catch anomalies before they reach downstream consumers.
    • Optimize BigQuery queries and models for cost and performance within your domain, escalating architectural tradeoffs to senior engineers when appropriate.
    • Collaborate with analysts and stakeholders to translate business data needs into well-scoped pipeline and modeling tasks.
    • Participate in on-call rotations, respond to pipeline incidents, and write clear postmortems.
    • Contribute to team documentation and runbooks so that your work is maintainable by others.
      
      Skills and experience

      Required:

      • 3–5 years of experience in data engineering or a closely related data infrastructure role.
      • Proven experience designing and implementing scalable data pipelines and warehouse architectures.
      • Strong expertise in Google Cloud Platform (BigQuery, Cloud Storage, Cloud Composer, Pub/Sub, Dataflow).
      • Hands-on experience with dbt (data build tool) — models, tests, macros, sources, and documentation — at production scale.
      • Experience building and maintaining data pipelines with Apache Airflow or a comparable workflow orchestration tool.
      • Strong proficiency in SQL, including advanced BigQuery SQL (window functions, partitioning, clustering, query optimization).
      • Proficiency in Python for data engineering tasks, including API integrations, data processing scripts, and custom operators.
      • Familiarity with data modeling concepts: star schema, dimensional modeling, slowly changing dimensions (SCD).
      • Experience with version control (Git) and collaborative development workflows (pull requests, code review).
      • Understanding of data quality, lineage, and observability best practices.
      • Startup or growth-stage mindset — comfortable with ambiguity, rapid iteration, and evolving priorities.
      • Excellent communication skills, with the ability to collaborate effectively across technical and non-technical teams

      Preferred:

      • Experience with Terraform or similar infrastructure-as-code tools for managing cloud data infrastructure.
      • Familiarity with streaming technologies such as GCP Pub/Sub, Dataflow, or Apache Kafka.
      • Knowledge of Looker, Tableau, or other BI tools and how data models power them.
      • Google Cloud Professional Data Engineer certification
        
        Why join us: 
        
        
      • Work on a modern, best-in-class GCP and BigQuery data stack with a high-performing team.
      • Influence data platform architecture decisions and grow into a senior or staff engineering role.
      • Competitive compensation, equity, and benefits with a culture that values engineering craft and continuous learning

As well as being a part of something exciting everyday, you will also receive the following benefits:

• Annual salary + bonus
• A remote first culture!
• Flex PTO 
• Health, Dental and Vision Insurance
• 13 Paid Holidays
• Company volunteer days

What we do!

NMI enables our partners with choice, and challenges the one-size-fits-all approach to payments. You've probably used NMI in the last 24 hours without even realizing it. We’re the platform that powers success for innovative tech created by SMBs, entrepreneurs and fintech startups. We’re creative problem solvers who help visionaries smash through boundaries and think beyond what’s possible so they can think about what’s next. But we’re not just built for the tech savvy. We democratize the latest payments technology so that everyone can realize the benefits of easy payments across the full spectrum of commerce. We’re all about enabling more payments in more ways and more places.

We believe that having a diverse group of employees strengthens both our work and our workplace. We’re focused on making NMI more diverse and welcoming with initiatives like having a dedicated Diversity, Equity & Inclusion action group, diversity goals for hiring, anonymized resume screening, affinity groups such as our Women's network and LGBTQ+ Network, open forums for discussions on diversity and social justice, and measuring inclusion and belonging as part of our regular employee engagement surveys.

Equal Opportunity

NMI is committed to providing equal employment opportunity for all persons regardless of race, color, religion, sex, age, marital status, national origin, sexual orientation or sexual identity, genetic information, citizen status (except those that do not have the legal right to be employed in the United States), disability, military service, service member, veteran status, or any other basis protected by applicable law.

Please be aware that all offers of employment are made subject to receipt of satisfactory background and financial checks.

Attention job applicants: Please note that in compliance with the data protection regulations within your jurisdiction, any personal information submitted with your job application may be collected and used by NMI for the purpose of recruitment and employment-related activities. By submitting your application, you acknowledge and provide explicit consent to the processing of your personal information as described in our privacy policy found on our website. For more information on how we process your information, please read our privacy policy here: https://www.nmi.com/legal/privacy-policy/

#LI-Remote

We are seeking a skilled Mid-Level Data Engineer to join our Data Platform team. At this level, you will be a hands-on executor and domain owner — responsible for building, maintaining, and improving the pipelines and data models that power analytics and business intelligence across the company. You will own specific areas of our BigQuery data warehouse end-to-end, delivering reliable data products within a framework set by senior and staff engineers.

This is not an architecture or strategy role — it is a role for someone who takes well-defined problems and executes them with high craft and reliability. You will work closely with data analysts, analytics engineers, and product teams, and are expected to grow toward greater technical ownership over time.

Key Duties

• Build and maintain production-grade ELT pipelines that ingest data from internal applications, third-party SaaS tools, and event streams into our BigQuery data warehouse.
• Own specific data domains end-to-end — from raw ingestion through to marts — ensuring your areas of the warehouse are accurate, tested, and well-documented.
• Write and maintain dbt models, tests, macros, and documentation within our established dbt project conventions and code review process.
• Develop and manage Airflow DAGs on Cloud Composer or other similar tools to orchestrate data workflows, following patterns and standards set by the team.
• Implement data quality checks and monitoring to catch anomalies before they reach downstream consumers.
• Optimize BigQuery queries and models for cost and performance within your domain, escalating architectural tradeoffs to senior engineers when appropriate.
• Collaborate with analysts and stakeholders to translate business data needs into well-scoped pipeline and modeling tasks.
• Participate in on-call rotations, respond to pipeline incidents, and write clear postmortems.
• Contribute to team documentation and runbooks so that your work is maintainable by others.
  
  Skills and experience

  Required:

  • 3–5 years of experience in data engineering or a closely related data infrastructure role.
  • Proven experience designing and implementing scalable data pipelines and warehouse architectures.
  • Strong expertise in Google Cloud Platform (BigQuery, Cloud Storage, Cloud Composer, Pub/Sub, Dataflow).
  • Hands-on experience with dbt (data build tool) — models, tests, macros, sources, and documentation — at production scale.
  • Experience building and maintaining data pipelines with Apache Airflow or a comparable workflow orchestration tool.
  • Strong proficiency in SQL, including advanced BigQuery SQL (window functions, partitioning, clustering, query optimization).
  • Proficiency in Python for data engineering tasks, including API integrations, data processing scripts, and custom operators.
  • Familiarity with data modeling concepts: star schema, dimensional modeling, slowly changing dimensions (SCD).
  • Experience with version control (Git) and collaborative development workflows (pull requests, code review).
  • Understanding of data quality, lineage, and observability best practices.
  • Startup or growth-stage mindset — comfortable with ambiguity, rapid iteration, and evolving priorities.
  • Excellent communication skills, with the ability to collaborate effectively across technical and non-technical teams

  Preferred:

  • Experience with Terraform or similar infrastructure-as-code tools for managing cloud data infrastructure.
  • Familiarity with streaming technologies such as GCP Pub/Sub, Dataflow, or Apache Kafka.
  • Knowledge of Looker, Tableau, or other BI tools and how data models power them.
  • Google Cloud Professional Data Engineer certification
    
    Why join us: 
    
    
  • Work on a modern, best-in-class GCP and BigQuery data stack with a high-performing team.
  • Influence data platform architecture decisions and grow into a senior or staff engineering role.
  • Competitive compensation, equity, and benefits with a culture that values engineering craft and continuous learning

As well as being a part of something exciting everyday, you will also receive the following benefits:

• Annual salary + bonus
• A remote first culture!
• Flex PTO 
• Health, Dental and Vision Insurance
• 13 Paid Holidays
• Company volunteer days

What we do!

NMI enables our partners with choice, and challenges the one-size-fits-all approach to payments. You've probably used NMI in the last 24 hours without even realizing it. We’re the platform that powers success for innovative tech created by SMBs, entrepreneurs and fintech startups. We’re creative problem solvers who help visionaries smash through boundaries and think beyond what’s possible so they can think about what’s next. But we’re not just built for the tech savvy. We democratize the latest payments technology so that everyone can realize the benefits of easy payments across the full spectrum of commerce. We’re all about enabling more payments in more ways and more places.

We believe that having a diverse group of employees strengthens both our work and our workplace. We’re focused on making NMI more diverse and welcoming with initiatives like having a dedicated Diversity, Equity & Inclusion action group, diversity goals for hiring, anonymized resume screening, affinity groups such as our Women's network and LGBTQ+ Network, open forums for discussions on diversity and social justice, and measuring inclusion and belonging as part of our regular employee engagement surveys.

Equal Opportunity

NMI is committed to providing equal employment opportunity for all persons regardless of race, color, religion, sex, age, marital status, national origin, sexual orientation or sexual identity, genetic information, citizen status (except those that do not have the legal right to be employed in the United States), disability, military service, service member, veteran status, or any other basis protected by applicable law.

Please be aware that all offers of employment are made subject to receipt of satisfactory background and financial checks.

Attention job applicants: Please note that in compliance with the data protection regulations within your jurisdiction, any personal information submitted with your job application may be collected and used by NMI for the purpose of recruitment and employment-related activities. By submitting your application, you acknowledge and provide explicit consent to the processing of your personal information as described in our privacy policy found on our website. For more information on how we process your information, please read our privacy policy here: https://www.nmi.com/legal/privacy-policy/

#LI-Remote