Senior Data Engineer

Senior Data Engineer

Position Overview

SmartAsset is seeking a seasoned Senior Data Engineer with 7+ years of hands-on experience to build and optimize the backbone of our data platform. This role involves designing and implementing high-impact, cloud-native solutions to enhance data reliability, reduce latency, and scale with our growing business. You will be instrumental in enabling data products, real-time analytics, and cross-functional decision-making by delivering clean, well-structured, and accessible data.

About SmartAsset

SmartAsset is a leading online destination for consumer-focused financial information and advice, dedicated to helping people make smart financial decisions. We reach an estimated 59 million people monthly (as of January 2025) through educational content, personalized calculators, and tools. Our SmartAsset Advisor Marketing Platform (AMP) connects consumers with fiduciary financial advisors. SmartAsset has been recognized on the Inc. 5000 (#2574 in 2023) and Deloitte Technology Fast 500™ (#250 in 2022) lists, and ranks on Y Combinator’s list of Top 100 Companies. In 2021, we completed a $110 million Series D funding round, valuing the company at over $1 billion.

Note: Other than application and licensing fees, SmartAsset did not provide compensation for the aforementioned awards.

About the Team

The Data Engineering team at SmartAsset builds and maintains 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 in Marketing, Product, Sales, and Finance. You will join a growing data organization comprising analysts, data scientists, and ML engineers who are at the forefront of AI/ML application within the company. As a Senior Data Engineer, you will collaborate cross-functionally to evolve our architecture, optimize data latency, and build robust solutions for data-driven decisions at scale.

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 Required

• 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.
• Experience with container orchestration services like ECS and EKS for deploying and managing data applications.

Skills/Experience Preferred

• Proven experience designing and building near real-time data processing systems.
• Experience with data observability tools for proactive monitoring of data quality, lineage, and pipeline health.
• Familiarity with modern data orchestration platforms such as Argo or Airflow.
• Hands-on experience with the full software development lifecycle (SDLC).

Employment Type:

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Location Type:

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Salary:

• [Salary Not Specified]