Sr. Data Engineer

Job DescriptionAbout the RoleWe 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)Key Responsibilities:Data Engineering & ArchitectureDesign and build scalable batch and streaming pipelines for ingestion, transformation, and consumption.Develop andoptimizeETL/ELT workflows using modern orchestration or transformation tools.Build microservices and data services using Python or Java Spring Boot,leveragingevent-drivenarchitecturesuch 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 EngineeringDesign 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 andmaintainCI/CD pipelines across cloud environments using Git-based workflows.Enterprise Platform IntegrationLearn 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.Supportintegration, workflow implementations, troubleshooting, and platform enhancements across multiple systems.Observability, Quality & ReliabilityImplement 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 & DeliveryWork directly with product and business teams to gather requirements, build prototypes, and deliver production-grade solutions.ProvideaccurateLOEs and contribute to architectural municate effectively with global and cross-functional teams.Drive engineering standards, documentation quality, and reusable frameworks across the novation & Emerging TechnologiesPrototype 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.Required Qualifications7+ 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 SQLexpertiseand 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 learnadditionalclouds as needed.Experience building microservices, APIs, and cloud-native data workflows.Proficiencywith Git, CI/CD, and modern DevOps practices.Strong technical curiosity and proven ability to learn new platforms, tools, andarchitecturequickly.Excellent communication, problem-solving, and cross-functional collaboration skills.A self-driven mindset with strong ownership and accountability.California Residents click below for Privacy Notice:

Created: 2026-01-30