Senior Data Platform Engineer

United States Digital Space LLC; Boston (MA); On-site; USD 150,000 - 215,000; Full time

Job summary

the company, based in Boston, seeks a Senior Data Platform Engineer to build and evolve the data platform, lakehouse, and real‑time data systems. You will partner with data engineers, ML platform engineers, software engineers, and data scientists to deliver scalable, production‑grade infrastructure.

You will own core services end to end, focusing on architecture, reliability, observability, and operational excellence, while advancing the use of AI-assisted development tools across the team.

Qualifications

• 5+ years of experience in data engineering, platform engineering, or software engineering with significant ownership of production data systems.
• Strong proficiency in Python and SQL. Java experience is nice to have.
• Experience designing and operating scalable data platforms, pipelines, or distributed data systems in production environments.
• Hands-on experience with Snowflake and modern cloud data infrastructure.
• Experience with AWS services such as S3, EKS, EMR, EC2, or related cloud-native infrastructure.
• Experience with orchestration frameworks such as Airflow or Prefect.
• Strong understanding of CI/CD, infrastructure as code, and DevOps practices for data platforms.
• Ability to independently drive technical projects and own systems end to end with a high degree of autonomy.
• Strong communication and collaboration skills, with the ability to work effectively across engineering and data teams.
• Commitment to leveraging AI-assisted development tools thoughtfully and effectively, while maintaining a high bar for engineering quality.

Responsibilities

• Design, build, and operate the core infrastructure and services that power the company’s data platform, including lakehouse, warehouse, and streaming systems.
• Improve the performance, reliability, and cost efficiency of our data systems, including Iceberg, Snowflake, and AWS-based data infrastructure.
• Build and enhance internal tooling, APIs, and automation that improve platform usability and developer experience for data engineers, analysts, and data scientists.
• Lead platform engineering best practices across CI/CD, infrastructure as code, testing, deployments, and operational readiness.
• Strengthen observability and operational excellence through monitoring, alerting, incident response, and continuous improvement of production systems.
• Partner cross-functionally with Data Science, Analytics, ML Platform, and Software Engineering teams to support scalable and efficient data workflows.
• Drive best practices for data architecture, pipeline design, governance, and platform usage across the company.
• Leverage AI tools to accelerate development, improve code quality, and enhance debugging and documentation workflows

Skills

Python

SQL

Java (nice to have)

Tools

Snowflake

AWS

Airflow

Prefect

Job description

At the company, we are on a mission to unlock human performance and healthspan. the company empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives.

We are seeking a Senior Data Platform Engineer to build and evolve the foundational infrastructure that powers our data platform, lakehouse, and real-time data systems. In this role, you will partner closely with data engineers, ML platform engineers, software engineers, and data scientists to design, develop, and operate the core services and workflows that enable reliable, scalable, and efficient data movement across the organization.

As a senior individual contributor, you will own critical parts of the platform end to end - from architecture and implementation to reliability, observability, and operational excellence. You will help shape the technical direction of the company’s data ecosystem, improve developer experience for internal data consumers, and ensure our systems can support analytics, machine learning, and product innovation at scale.This role requires a strong ownership mindset, the ability to operate with minimal guidance, and a focus on delivering production grade systems.

You are also expected to actively leverage AI assisted development tools to improve speed, quality, and maintainability, and to help set the standard for effective AI usage across the team.

RESPONSIBILITES:

• Design, build, and operate the core infrastructure and services that power the company’s data platform, including lakehouse, warehouse, and streaming systems.

• Improve the performance, reliability, and cost efficiency of our data systems, including Iceberg, Snowflake, and AWS-based data infrastructure.

• Build and enhance internal tooling, APIs, and automation that improve platform usability and developer experience for data engineers, analysts, and data scientists.

• Lead platform engineering best practices across CI/CD, infrastructure as code, testing, deployments, and operational readiness.

• Strengthen observability and operational excellence through monitoring, alerting, incident response, and continuous improvement of production systems.

• Partner cross-functionally with Data Science, Analytics, ML Platform, and Software Engineering teams to support scalable and efficient data workflows.

• Drive best practices for data architecture, pipeline design, governance, and platform usage across the company.

• Leverage AI tools to accelerate development, improve code quality, and enhance debugging and documentation workflows

QUALIFICATIONS:

• 5+ years of experience in data engineering, platform engineering, or software engineering with significant ownership of production data systems.

• Strong proficiency in Python and SQL. Java experience is nice to have.

• Experience designing and operating scalable data platforms, pipelines, or distributed data systems in production environments.

• Hands-on experience with Snowflake and modern cloud data infrastructure.

• Experience with AWS services such as S3, EKS, EMR, EC2, or related cloud-native infrastructure.

• Experience with orchestration frameworks such as Airflow or Prefect.

• Strong understanding of CI/CD, infrastructure as code, and DevOps practices for data platforms.

• Ability to independently drive technical projects and own systems end to end with a high degree of autonomy.

• Strong communication and collaboration skills, with the ability to work effectively across engineering and data teams.

• Commitment to leveraging AI-assisted development tools thoughtfully and effectively, while maintaining a high bar for engineering quality.

This role is based in the the company office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.

the company is an Equal Opportunity Employer and participates inE-verifyto determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

The the company compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.

At the company, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of the company and share in the company’s long-term growth and success.

The U.S. base salary range for this full-time position is $150,000-$215,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.

In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.

These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Learn more about the company.