Data Engineer

<p><strong>About SmartAsset</strong></p> <p>SmartAsset is an online destination for consumer-focused financial information and advice, whose mission is helping people make smart financial decisions, reaching over an estimated 59 million people each month (as of January 2025) through our educational content and personalized calculators and tools. To extend our mission, we also operate SmartAsset Advisor Marketing Platform (AMP), which helps connect consumers with fiduciary financial advisors.SmartAsset has earned recognition on the Inc. 5000 (#2574 in 2023) and Deloitte Technology Fast 500™ (#250 in 2022) lists. Currently, SmartAsset ranks on Y Combinator’s list of Top 100 Companies. A successful $110 million Series D funding round in 2021 valued the company at over $1 billion.</p> <p><em>*Other than application and licensing fees, SmartAsset did not provide compensation for the aforementioned awards.</em></p> <h3><strong>About the team</strong></h3> <p>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.</p> <p>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 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.</p> <p><strong>About the Job</strong></p> <p>SmartAsset is looking for a Data Engineer with 3+ 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.</p> <p><strong>Responsibilities:</strong></p> <ul> <li>Design, implement, and maintain scalable data engineering solutions following Agile methodology.</li> <li>Develop and manage reliable data integrations with external vendors and organizations (including API integrations).</li> <li>Collaborate closely with Data Analysts, Data Scientists, DBAs, and cross-functional teams to understand requirements and deliver high-quality data solutions.</li> <li>Take ownership of assigned components and deliverables within larger technical projects.</li> <li>Contribute to improving the quality, security, efficiency, and scalability of data pipelines and infrastructure.</li> </ul> <p><strong>Skills/Experience You Have:</strong></p> <ul> <li style="font-weight: 400;"><span style="font-weight: 400;">Bachelor of Science degree in Computer Science or equivalent.</span></li> <li>3 - 5 years of experience building and maintaining ETL/ELT pipelines.</li> <li>2+ years of Python development experience, including building and maintaining production-grade data services (e.g., FastAPI or similar frameworks).</li> <li>Strong SQL skills, including performance tuning and query optimization.</li> <li>Hands-on experience with dbt, including developing models and managing incremental tables.</li> <li>Practical experience with Snowflake, including data modeling and query optimization.</li> <li>Experience with AWS data services such as S3, Redshift, Lambda, or similar tools for building and operating data workflows.</li> </ul> <p><strong>Skills/Experience Preferred:</strong></p> <ul> <li style="font-weight: 400;">Experience working with near real-time or streaming data systems.</li> <li style="font-weight: 400;">Familiarity with data observability or monitoring tools.</li> <li style="font-weight: 400;">Exposure to orchestration platforms such as Airflow or Argo.</li> <li style= ... (truncated, view full listing at source)