Data Platform Engineer

The Data Platform Engineer designs, builds, and evolves the data platform that powers analytics, reporting, and downstream integrations across DMSi products. This role owns the pipelines, schemas, and provisioning workflows that move data reliably from source systems into a scalable, multi-tenant analytics platform, and partners closely with database administration, infrastructure, and product teams to make that data available, accurate, and performant.

RESPONSIBILITIES AND DUTIES

• Design and build data pipelines that move data reliably from source systems into the analytics platform, using change data capture, event streaming, and related integration patterns.
• Design, implement, and maintain PostgreSQL schemas and data models that support scalable, multi-tenant analytics.
• Build and maintain the dashboard data layer that powers customer-facing analytics and reporting.
• Develop and maintain per-customer data provisioning workflows so new customers and data sources onboard onto the platform consistently.
• Apply infrastructure-as-code practices to provision, configure, and manage data platform environments in a repeatable and auditable way.
• Monitor data pipeline health, performance, and data quality, and troubleshoot and resolve latency, throughput, and accuracy issues.
• Partner with product management and engineering teams to translate reporting and analytics requirements into data platform capabilities.
• Collaborate with database administration and infrastructure teams to ensure the data platform integrates cleanly with the broader hosting environment and follows established security and access control standards.
• Document data platform architecture, data flows, and operational procedures to support ongoing maintenance, on-call response, and knowledge sharing across the team.
• Evaluate tools, platforms, and approaches that improve the reliability, scalability, and performance of the data platform, and recommend adoption where warranted.

KNOWLEDGE, SKILLS, AND ABILITIES

Strong hands-on experience with PostgreSQL, including schema design, query optimization, and data modeling for analytical workloads.

Experience with Kafka or a comparable event streaming or message platform, including change data capture pipeline design.

Experience with cloud infrastructure and infrastructure-as-code tooling.

Proficiency in at least one programming or scripting language, such as Python, for pipeline and automation development.

Familiarity with data modeling principles for multi-tenant, analytics-oriented systems.

Working knowledge of data security and access control practices appropriate to a multi-tenant analytics environment.

Strong problem-solving skills and the ability to work independently through ambiguous technical problems.

Clear written and verbal communication skills, including the ability to document technical designs for both technical and non-technical audiences.

Experience with monitoring and observability tooling is a plus.

EDUCATION AND EXPERIENCE

Bachelor’s Degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.

Three or more years of experience building and operating data pipelines, data platforms, or database-backed systems in production.

WORK ENVIRONMENT & PHYSICAL DEMANDS

Normal office environment with use of computers and telephone systems; no unusual physical demands.

Travel to customer locations as needed, including overnight stays, business air travel, and car rentals.

May require occasional off-hours availability to support on-call rotations or planned maintenance windows.