Senior Data Engineer

Compensation $140,000–$160,000 base + bonus Work Authorization Must be authorized to work in the U.S. without sponsorship (now or in the future) About the Company This established financial services organization is investing heavily in the next generation of its enterprise data platform. The team is building a modern cloud-native analytics ecosystem designed to support scalable data products, advanced analytics, and AI initiatives across the business. This is an opportunity to join a well-funded modernization effort where you\'ll help define engineering standards, influence architecture, and build production-grade data solutions using today\'s leading cloud technologies. The engineering culture emphasizes technical excellence, ownership, automation, and collaboration, giving engineers the opportunity to make a lasting impact while working on highly visible initiatives. About the Role This is not a traditional ETL maintenance role. As a Senior Data Engineer, you\'ll help build a modern analytics platform from the ground up, designing scalable ingestion pipelines, transformation frameworks, and cloud-native data architectures that enable analytics, reporting, and AI across the enterprise. You'll work alongside platform engineers, architects, analytics teams, and business stakeholders to build production-ready data solutions while helping establish engineering best practices for the broader organization. Whether your strength is data ingestion with Fivetran or analytics engineering with dbt and Snowflake, you\'ll have the opportunity to own critical components of a rapidly evolving data platform. Key Responsibilities Design and build scalable ELT pipelines using modern cloud technologies Develop and maintain production-ready data transformation frameworks with dbt Design Snowflake data models that support analytics, reporting, and downstream applications Build and optimize data ingestion pipelines using Fivetran and cloud-native integration patterns Develop reusable, well-tested Python and SQL solutions for large-scale data processing Implement CI/CD practices and Infrastructure as Code to improve deployment reliability Establish data quality, observability, governance, and operational monitoring standards Partner with architects, platform engineers, analytics teams, and business stakeholders to deliver enterprise-scale data solutions Evaluate emerging technologies and contribute to the long-term evolution of the data platform Mentor engineers and promote engineering best practices across the team Must Haves 7+ years of Data Engineering experience building production-grade data platforms Strong Python and advanced SQL skills Hands-on experience with dbt (required) Production experience with Snowflake Modern cloud experience (AWS preferred) Experience building and supporting enterprise data warehouses Strong understanding of CI/CD, version control, and software engineering best practices Ability to lead technical discussions and influence architectural decisions Excellent communication skills with a collaborative, ownership-driven mindset Nice to Have Fivetran Terraform or Infrastructure as Code PySpark Kafka or streaming data platforms Data platform modernization or cloud migration experience Experience building analytics-ready data products Why Join Help build a next-generation enterprise analytics ecosystem from the ground up Work on a greenfield-style modernization initiative using modern cloud technologies Join a collaborative engineering organization where technical leadership is valued Influence architecture, engineering standards, and the future direction of the data platform Work with technologies including Snowflake, dbt, Fivetran, Python, AWS, and Terraform Hybrid schedule (4 days onsite) with long-term career growth in a stable enterprise environment #J-18808-Ljbffr Harnham