Sr. Data Engineer
About The Position
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)
Requirements
- 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 DevOps 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.
Responsibilities
- 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.
- Cloud & Platform Engineering 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, BigQuery , 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.
- Enterprise Platform Integration 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.
- Observability, Quality & Reliability 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.
- Collaboration & Delivery 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.
- Innovation & Emerging Technologies 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.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
