Posted at: 18 June
Senior Data Engineer
Company
Versapay is a Miami-based fintech B2B company specializing in accounts receivable automation software and cash application solutions for mid-sized businesses in the U.S. and Canada.
Remote Hiring Policy:
Versapay hires remotely from various locations within North America, with team members based in the U.S. and Canada. The company supports collaboration across time zones.
Job Type
Full-time
Full-timeAllowed Applicant Locations
United States, Canada
United States, CanadaSalary
$130,000 to $150,000 per year
$130,000 to $150,000 per yearJob Description
The Analytics team is evolving our enterprise capabilities from foundational governance into a robust data platform, safely accelerating strategic AI enablement and delivering high-margin commercial data products. As a Senior Data Engineer, you will be pivotal in optimizing and scaling our foundational Snowflake architecture while aggressively pushing toward agentic engineering and machine learning operations. You will operate as a full-stack generalist within the engineering pod, sharing cross-functional responsibility for pipeline resilience, advanced observability, and the deployment of intelligent semantic models that directly feed our product ecosystem.
Reports To: Manager of Data Engineering
What You'll Do:
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Architect for the Future: Optimize our existing Snowflake architecture, establishing strict environmental isolation and scalable structures that prepare our data for eventual downstream commercialization and product offerings.
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Drive Agentic Engineering: Leverage tools like Snowflake Cortex, Cursor, and UiPath to automate workflows, build semantic models, and deploy agents that accelerate time-to-value.
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Establish Data Observability: Implement and manage robust data quality and observability frameworks to ensure pipeline reliability and proactive issue resolution.
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Operationalize Machine Learning: Design and maintain MLOps pipelines to support the seamless rollout, monitoring, and lifecycle management of ML models directly within Snowflake.
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Execute Shared Ownership: Partner closely with your peers under the Data Engineering Manager to share responsibilities across pipeline management, MLOps, and architecture, avoiding siloed knowledge and ensuring comprehensive team coverage.
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Model for Enterprise Utility: Synthesize disparate operational entities into a unified, enterprise-wide semantic model that supports both internal analytics and future data monetization efforts.
Qualifications
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5+ years of Data Engineering experience with a deep, specialized focus on Snowflake's advanced features (e.g., RBAC, materialized views, dynamic tables, Snowpipe, stored procedures).
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Advanced proficiency in SQL and Python, with a strong foundation in applying software engineering best practices to ELT processes.
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Observability Expertise: Hands-on experience implementing data observability and monitoring platforms (such as DataDog) to manage data quality at scale.
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AI & MLOps Exposure: Demonstrated experience using AI-assisted development tools (e.g., Cursor, Cortex) and familiarity with MLOps principles for productionalizing machine learning models.
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Pipeline Management: Experience building and maintaining resilient, low-touch data pipelines using modern integration and orchestration tools (e.g., Fivetran, AWS Glue, AWS Lambda).
What You'll Bring To The Team:
- Technical Competency: Advanced SQL skills, proficiency with Python/R, and experience with BI tools. Focus on self-sufficiency and leveraging AI tools to accelerate development.
- "Builder" Mentality: An ability to thrive in fast-paced environments with a track record of defining and executing high-impact initiatives. A desire to solve complex problems, remediate technical debt, and find creative solutions for scaling our platform.
- Business Acumen: Strong business acumen with a proven ability to translate complex data analysis into strategic recommendations. Adept at identifying key drivers and influencing decision-making. You understand the business behind the data and the path to commercialization.
- Empathetic Collaboration: Assertive with humility – able to communicate both persuasively and positively. Maintain high standards for verbal and written communication while seamlessly sharing domain responsibilities across the engineering pod.
- Trusted Advisor: Possesses a high degree of integrity, the relentless pursuit of truth, and an ability to inspire change, particularly in championing data quality and observability standards.
What Will Make You Stand Out:
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Deep domain expertise navigating complex merchant payment ecosystems (e.g., Adyen), operating under rigorous enterprise data governance and security standards.
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Proven ability to architect the translation of high-velocity transactional events into highly optimized, columnar analytical architectures.
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Direct experience architecting data products for commercialization, external endpoints, or embedded analytics within a SaaS platform.