AssetWatch serves global manufacturers by powering manufacturing uptime through the delivery of an unparalleled condition monitoring experience, with a passion to care about the assets our customers care for every day. We are a devoted and capable team that includes world-renowned engineers and distinguished business leaders united by a common goal – To build the future of predictive maintenance. As we enter the next phase of rapid growth, we are seeking people to help lead the journey.
Director of Data Platforms & Governance
AssetWatch serves global manufacturers by powering manufacturing uptime through the delivery of an unparalleled condition monitoring experience, with a passion to care about the assets our customers care for every day. We are a devoted and capable team that includes world-renowned engineers and distinguished business leaders united by a common goal – To build the future of predictive maintenance. As we enter the next phase of rapid growth, we are seeking people to help lead the journey.
With a bleeding edge tech stack, we have a unique opportunity to scale how we operate as a data-driven and AI-ready organization. If you love the startup life and the sense of urgency where the platforms you build materially impact the organization’s growth, let us talk.
The Director of Data Platforms & Governance owns data as a first-class company asset, ensuring it is reliable, well-governed, discoverable, and ready to power analytics, AI, and product innovation.
This leader defines the strategy, architecture, and operating model for AssetWatch’s data platform while building and leading the team responsible for delivering it. The role works closely with Product, Engineering, Analytics, AI, Security, and Enterprise Applications leadership to ensure the company’s systems and data evolve together.
What You'll Do
Define Data Platform Strategy: In partnership with senior leadership, define the vision, roadmap, and operating model for AssetWatch’s data platform, ensuring it supports analytics, product development, and AI initiatives across the organization.
Lead the Data Platforms Organization: Build, lead, and develop the data platforms team, establishing clear goals, accountability, and performance expectations. Develop managers and engineers while fostering a culture of ownership, collaboration, and continuous improvement.
Set Organizational OKRs: Partner with executive leadership to define strategic OKRs for the data platform organization and translate them into measurable goals for teams and individuals.
Own Data as a Company Asset: Establish the governance framework that ensures data across the organization is well-defined, trusted, and properly managed, including dataset ownership, data definitions, lineage, access controls, and lifecycle management.
Data Platform Architecture: Design and evolve AssetWatch’s cloud data platform using AWS technologies such as S3, Glue, Athena, Redshift, and Lambda to support scalable analytics, reporting, and AI workloads through MCPs.
Data Ingestion & Pipelines: Oversee the development and reliability of data pipelines ingesting information from product telemetry, APIs, and enterprise SaaS systems.
Curated Data & Data Modeling: Lead the creation of trusted datasets used for reporting, operational decision making, and machine learning.
AI-Ready Data Infrastructure: Ensure the company’s data platform is structured to support AI and machine learning initiatives by enabling reliable, well-modeled data inputs for ML pipelines and advanced analytics.
Enterprise Systems Data Integration: Partner closely with Enterprise Applications leadership to ensure systems such as Salesforce, finance platforms, and customer success tools integrate cleanly into the data platform.
Data Quality & Reliability: Establish monitoring and operational processes that ensure data accuracy, pipeline reliability, and data freshness.
Security, Privacy & Compliance: Work with IT and Security teams to ensure the data platform meets SOC2 and privacy requirements including access control, encryption, audit logging, and retention policies.
Operational Efficiency: Eliminate manual reporting workflows and redundant integrations by creating scalable, automated data pipelines and shared data models.
Cross-Functional Leadership: Lead highly visible initiatives that align teams across engineering, product, operations, and leadership to improve data reliability and organizational decision-making.
Who You Are
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
10+ years of experience in data engineering, analytics platforms, or data infrastructure roles, including experience leading teams.
Experience defining and executing data platform strategy in a cloud environment.
Strong experience building and operating data platforms using AWS technologies such as S3, Glue, Athena, Redshift, and Lambda.
Experience building and managing teams responsible for data engineering, analytics infrastructure, or data platforms.
Strong experience designing ETL/ELT pipelines that integrate data from APIs, SaaS systems, and product telemetry.
Experience implementing data governance frameworks, including dataset ownership models, data definitions, and access controls.
Strong SQL and data modeling expertise, with experience building curated datasets used across analytics and operational reporting.
Experience integrating data from enterprise business systems, particularly:
- Salesforce
- Finance and operational reporting systems
- Customer Success or support platforms
Experience with NetSuite or similar ERP systems is a strong plus.
Experience supporting analytics, BI, data science, or AI/ML teams with scalable data infrastructure.
Strong leadership and communication skills with the ability to influence cross-functional stakeholders and executive leadership.
Ability to operate with high autonomy, exercising wide latitude in determining objectives and approaches to complex initiatives.
Proven ability to build high-performing teams, hold teams accountable for outcomes, and deliver against strategic commitments.
#LI-REMOTE
The base salary range for this full-time position is posted below, plus equity and benefits. Variable pay, bonuses, and other cash compensation will be discussed throughout the interview process.
The salary range was determined by role, level, and location. Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range applicable to your location during the hiring process.
AssetWatch is a remote-first company that puts people at the center of everything we do. We want our team members to thrive - that’s why we offer a range of benefits and perks designed to support your well-being, growth, and work-life balance.
- Competitive compensation package including stock options
- Flexible work schedule
- Comprehensive benefits including retirement plan match
- Opportunity to make a real impact every day
- Work with a dynamic and growing team
- Unlimited PTO
Skills Required
- 10+ years of experience in data engineering, analytics platforms, or data infrastructure roles
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field
- Strong experience building and operating data platforms using AWS technologies
- Experience implementing data governance frameworks
- Strong SQL and data modeling expertise
- Experience integrating data from enterprise business systems
- Experience with NetSuite or similar ERP systems
What We Do
AssetWatch provides an end-to-end condition monitoring solution for industrial organizations, focusing on predictive maintenance. Their platform combines vibration, temperature, and oil analysis data with AI-driven analytics and expert insights to detect equipment issues and prevent downtime.
