Senior Data Engineer

Description:

SmartAsset’s Data Engineering team builds and maintains the scalable, low-latency systems that power data access across the company. Our platform supports real-time and batch data needs for analytics, reporting, and machine learning, serving teams across Marketing, Product, Sales, and Finance.

You’ll be part of a growing data organization that includes analysts, data scientists, and ML engineers that are at the forefront of AI/ML application for the company. As a Senior Data Engineer, you'll work cross-functionally to evolve our architecture, optimize data latency, and build robust solutions that enable data-driven decisions at scale.

About The Job

SmartAsset is looking for a seasoned Senior Data Engineer with 7+ years of hands-on experience to help build and optimize the backbone of our data platform. In this role, you’ll design and implement high-impact, cloud-native solutions that improve data reliability, reduce latency, and scale with our growing business. You’ll play a key role in enabling data products, real-time analytics, and cross-functional decision-making by delivering clean, well-structured, and accessible data.

Responsibilities

Architect, design, implement, and operate end-to-end data engineering solutions using Agile methodology.
 

• Develop and manage robust data integrations with external vendors and organizations (including complex API integrations).
• Collaborate closely with Data Analysts, Data Scientists, DBAs, and cross-functional teams to understand requirements and deliver high-impact data solutions.
• Lead and take ownership of assigned technical projects in a fast-paced environment.
• Drive continuous improvement in the quality, security, efficiency, and scalability of our data pipelines and infrastructure.
   

Skills/Experience You Have
 

• Bachelor of Science degree in Computer Science or equivalent practical experience.
• 4+ years of dedicated experience building and maintaining complex ETL/ELT pipelines.
• 3+ years of Python development experience, specifically building production-grade data APIs using FastAPI or similar frameworks.
• Strong expertise in SQL, including advanced query optimization and performance tuning.
• Expert-level proficiency in dbt implementation, including managing models, macros, and incremental and dynamic tables.
• Extensive hands-on experience with Snowflake, including performance optimization, data recovery using Time Travel, and advanced data modeling techniques.
• Practical experience with key AWS data services such as Kinesis, Firehose, Redshift, Spectrum, Elastic MapReduce, and Lambda; and container orchestration services like ECS and EKS for deploying and managing data applications.