Job description

Job title: Staff Data Engineer Reports to: Director, Data Engineering Department: Central Services Location: Remote About Priority: Priority Commerce is a leading financial technology company on a mission to deliver a personalized, easy-to-adopt financial toolset that accelerates cash flow and optimizes working capital for businesses. Our vision is to eliminate the barriers to unlocking revenue - empowering businesses to grow faster and operate smarter. We achieve this through the Priority Commerce Engine, an innovative platform that combines payables, acquiring, and banking and treasury solutions. This unified approach allows businesses to streamline financial operations, reduce unnecessary costs, and uncover new revenue opportunities. At Priority Commerce, we're driven by results. We expect our people to be known for results - bringing expertise, momentum, and relentless focus to every challenge, helping our clients and each other thrive. About the Role: The Staff Data Engineer is a senior individual contributor responsible for designing and evolving scalable data architecture across Priority Holdings’ payments and commerce ecosystem. This role provides technical leadership across data ingestion, processing, Snowflake platform capabilities, data delivery, and data products, while helping establish engineering standards and reusable patterns across teams. You will work on complex, cross-domain problems that require strong technical judgment, influence architecture and platform direction, and enable multiple engineering teams to deliver reliable, secure, and cost-effective data solutions. The role also provides an opportunity to shape emerging capabilities in AI, automation, and MCP-enabled data access as the organization expands its data platform strategy. Responsibilities: • Leads the technical design of large-scale data systems, pipelines, and platform capabilities across multiple domains and engineering teams. • Defines reusable architecture patterns, engineering standards, and best practices for ingestion, transformation, orchestration, data quality, and data delivery. • Designs scalable solutions across Snowflake and supporting cloud technologies with a focus on reliability, performance, maintainability, and cost efficiency. • Partners with Data Engineering, Analytics Engineering, QA, Software Engineering, and business teams to translate complex requirements into sustainable technical solutions. • Provides technical leadership for internal and external data ingestion patterns, including batch, CDC, streaming, APIs, and file-based integrations. • Drives architecture for outbound data delivery through data sharing, APIs, SFTP, cross-cloud integrations, and other distribution mechanisms. • Supports the evolution of data products such as Reporting Platform, DataBridge, AI-enabled applications, and MCP-based data services. • Establishes and improves engineering practices for observability, monitoring, automated testing, data quality, CI/CD, and operational readiness. • Identifies platform limitations, technical debt, and scalability risks, and drives long-term solutions rather than tactical fixes. • Leads technical reviews for high-impact initiatives and ensures architectural decisions are aligned with enterprise standards and long-term platform direction. • Mentors senior and junior engineers through design reviews, technical guidance, and knowledge sharing. • Partners with engineering and business leadership on roadmap planning, architecture decisions, technical tradeoffs, and investment priorities. • Supports complex production incidents and drives root-cause resolution, prevention, and improvements to platform reliability. • Evaluates emerging technologies and introduces new approaches when they provide measurable improvements in scalability, automation, developer productivity, or business capability. What Success Looks Like: • Complex data initiatives are delivered using scalable, reusable, and well-governed architectural patterns. • Engineering teams benefit from clearer standards, stronger technical guidance, and reduced duplication across implementations. • Data pipelines and platform capabilities demonstrate improved reliability, observability, scalability, and operational readiness. • Technical decisions balance immediate delivery requirements with long-term platform sustainability and cost efficiency. • Cross-team architecture issues and ambiguous technical problems are resolved with clear direction and sound engineering judgment. • Senior and junior engineers become more effective through mentorship, design guidance, and reusable frameworks. • Data products and downstream consumers receive trusted, timely, and well-supported data through standardized platform capabilities. • Platform improvements reduce manual effort, recurring incidents, and technical debt. • The role is viewed as a trusted technical partner by engineering teams, leadership, and cross-functional stakeholders. • New capabilities in AI, automation, and MCP are introduced with appropriate security, governance, reliability, and architectural discipline. Candidate Requirements: Required • 8 ~ 12 years of experience in data engineering, software engineering, data platform engineering, or a related technical field. • Deep expertise in data architecture, distributed data processing, data warehousing, and large-scale data platform design. • Strong hands-on experience with Snowflake, including architecture, performance optimization, security, governance, and cost management. • Strong data querying skills and coding proficiency in Python, Java, or similar programming languages. • Strong experience with data modeling, ETL/ELT architecture, workflow orchestration, and performance optimization. • Experience designing and operating production-grade batch, streaming, or CDC-based data pipelines. • Strong experience with cloud-based data platforms and modern data engineering architectures. • Demonstrated ability to design scalable technical solutions across multiple systems and domains. • Experience establishing engineering standards, reusable frameworks, or architecture patterns adopted by multiple teams. • Strong understanding of data quality, observability, monitoring, CI/CD, and operational reliability. • Demonstrated ability to operate independently on highly ambiguous and complex technical problems. • Experience mentoring engineers and influencing technical decisions without direct management authority. • Strong communication skills with the ability to explain complex technical concepts, tradeoffs, and recommendations to technical and non-technical stakeholders. • Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience. Preferred • Experience with AWS data services, distributed processing technologies, and event-driven architectures. • Experience with technologies such as Kafka, Debezium, Spark/PySpark, Airflow, or similar platforms. • Experience designing external data sharing and delivery solutions across Snowflake, APIs, SFTP, and cross-cloud environments. • Experience with data platforms supporting fintech, payments, commerce, financial services, or other highly regulated environments. • Familiarity with AI/ML data architectures, AI-enabled applications, agentic workflows, or MCP-based integrations. • Experience designing platforms or frameworks that enable self-service data engineering or workflow automation. • Experience with governance, lineage, metadata management, access controls, and secure data-sharing patterns. • Experience leading major modernization, migration, or platform transformation initiatives. • Master's degree in Computer Science, Engineering, Data Science, or a related technical discipline. Work Environment & Culture: We believe that performance and experience go hand in hand - an exceptional employee experience is earned through contribution . We are a results driven team, grounded in our core values: ownership, authenticity, service, trust, innovation, and camaraderie. Our culture is built for those who want to make an impact. We challenge each other to grow, celebrate progress, and support one another through shared goals and real connection. Whether you're building technology, serving clients, or supporting internal teams, you’ll be part of a company that empowers you to perform at your best and be known for results. Compensation and Benefits: Compensation range: $145k-$190k We invest in the whole employee - personally and professionally. Our benefits package is designed to support your well-being, growth, and success - both inside and outside of work. Financial Wellness • Bonus programs • 401(k) match • Employee Stock Purchase Program (ESPP) • HSA and FSA options • Financial wellness resources and employee discount programs Health & Well-being • Medical, dental, and vision coverage • Mental health support for employees and dependents through Lyra Health • Family planning and women’s health benefits through Carrot • Gym membership reimbursement and virtual wellness programs (including yoga) Time Off • 3 weeks PTO to start, with unlimited PTO after year one Growth & Development • Education expense reimbursement • Leadership development programs • Certified Payments Professional (CPP) certification support We believe great performance starts with feeling supported - and we’ve built our benefits with that in mind. Traditional Physical Requirements: • Requires prolonged sitting, standing, bending, stooping and stretching. • Requires the ability to lift 10 pounds. • Requires eye-hand coordination, manual dexterity and a normal range of hearing and vision (with or without correction). Join our team at Priority Technology Holdings, Inc. and be part of a dynamic and innovative company that is transforming the financial technology landscape. Together, we can shape the future of payments and banking solutions while providing unmatched value to our clients.

Requirements

Must-haves

Job title: Staff Data Engineer
Reports to: Director, Data Engineering
Department: Central Services
Location: Remote
Leads the technical design of large-scale data systems, pipelines, and platform capabilities across multiple domains and engineering teams.
Defines reusable architecture patterns, engineering standards, and best practices for ingestion, transformation, orchestration, data quality, and data delivery.
Designs scalable solutions across Snowflake and supporting cloud technologies with a focus on reliability, performance, maintainability, and cost efficiency.
Partners with Data Engineering, Analytics Engineering, QA, Software Engineering, and business teams to translate complex requirements into sustainable technical solutions.
Provides technical leadership for internal and external data ingestion patterns, including batch, CDC, streaming, APIs, and file-based integrations.
Drives architecture for outbound data delivery through data sharing, APIs, SFTP, cross-cloud integrations, and other distribution mechanisms.
Supports the evolution of data products such as Reporting Platform, DataBridge, AI-enabled applications, and MCP-based data services.
Establishes and improves engineering practices for observability, monitoring, automated testing, data quality, CI/CD, and operational readiness.
Identifies platform limitations, technical debt, and scalability risks, and drives long-term solutions rather than tactical fixes.
Leads technical reviews for high-impact initiatives and ensures architectural decisions are aligned with enterprise standards and long-term platform direction.

Nice-to-haves

Experience with AWS data services, distributed processing technologies, and event-driven architectures.
Experience with technologies such as Kafka, Debezium, Spark/PySpark, Airflow, or similar platforms.
Experience designing external data sharing and delivery solutions across Snowflake, APIs, SFTP, and cross-cloud environments.
Experience with data platforms supporting fintech, payments, commerce, financial services, or other highly regulated environments.
Familiarity with AI/ML data architectures, AI-enabled applications, agentic workflows, or MCP-based integrations.
Experience designing platforms or frameworks that enable self-service data engineering or workflow automation.
Experience with governance, lineage, metadata management, access controls, and secure data-sharing patterns.
Experience leading major modernization, migration, or platform transformation initiatives.
Master's degree in Computer Science, Engineering, Data Science, or a related technical discipline.
Bonus programs

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aici/cdpythonjavaawsmlgo

Platform: adp-workforce-now
Effort: medium

Benefits

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Dental

Vision

401(K)

Pto

Wellness