Sr. Data Engineer

About the Role

We are seeking a Senior Data Engineer with strong hands-on experience in building scalable data pipelines, microservices, and modern cloud-native data solutions. Beyond traditional data engineering, this role requires someone with high learning agility, a willingness to adopt new platforms, and strong curiosity for enterprise systems that support data operations.

This individual will serve as a key onsite engineering partner for Product, Business, and cross-functional teams. The engineer will build data workflows, integrate with enterprise platforms, and support end-to-end data lifecycle needs across the organization.

This position is 4 days in office, 1 day remote per week, based at our corporate headquarters in Raleigh, North Carolina (North Hills)

• Data Engineering & Architecture
  • Design and build scalable batch and streaming pipelines for ingestion, transformation, and consumption.
  • Develop and optimize ETL/ELT workflows using modern orchestration or transformation tools.
  • Build microservices and data services using Python or Java Spring Boot, leveraging event-driven architecture such as Kafka.
  • Apply strong SQL skills to develop analytical datasets, transformations, and modeling patterns.
  • Build reusable, modular engineering components that support long-term maintainability.

• Design and build cloud-native solutions using any major cloud platform (AWS, Azure, GCP) and be comfortable adopting new cloud services as organizational needs evolve.
• Work with cloud data warehouses (e.g., Snowflake, Big Query, Redshift, Synapse) for modeling, performance tuning, and data operations.
• Implement scalable, secure, and observable cloud data workflows using a cloud-neutral architectural mindset.
• Develop and maintain CI/CD pipelines across cloud environments using Git-based workflows.

• Learn and support enterprise data systems and integration platforms used across the organization.
• Serve as the primary onsite engineering resource, partnering closely with Product, Business, and Data teams.
• Support integration, workflow implementations, troubleshooting, and platform enhancements across multiple systems.

• Implement strong observability across pipelines and services, including logging, metrics, dashboards, tracing, and alerting.
• Build robust data quality checks, validation rules, error handling, and resiliency patterns.
• Ensure data pipelines and microservices meet reliability, recoverability, and performance standards.

• Work directly with product and business teams to gather requirements, build prototypes, and deliver production-grade solutions.
• Provide accurate LOEs and contribute to architectural decisions.
• Communicate effectively with global and cross-functional teams.
• Drive engineering standards, documentation quality, and reusable frameworks across the team.

• Prototype solutions using AI/LLM tooling, automation frameworks, and next-generation data technologies.
• Stay current with modern data engineering and cloud-native patterns.
• Bring forward-looking ideas that align with the future direction of the data platform ecosystem.

• 7+ years of hands-on experience in data engineering.
• Strong experience with Python and/or Java Spring Boot.
• Deep experience with Kafka or similar streaming platforms.
• Strong SQL expertise and experience with at least one cloud data warehouse (Snowflake preferred).
• Hands-on experience with at least one major cloud (AWS, Azure, or GCP) with a willingness to learn additional clouds as needed.
• Experience building microservices, APIs, and cloud-native data workflows.
• Proficiency with Git, CI/CD, and modern Dev Ops practices.
• Strong technical curiosity and proven ability to learn new platforms, tools, and architecture quickly.
• Excellent communication, problem-solving, and cross-functional collaboration skills.
• A self-driven mindset with strong ownership and accountability.

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We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age national origin, religion, sexual orientation, gender identity, status as a veteran and basis of disability or any other federal, state or local protected class.