Analytics Engineer

Forward Financing•Boston, MA

4d•$110,000 - $130,000•Remote

About The Position

Forward Financing is a financial technology company based in Boston, Massachusetts with team members throughout the United States, Dominican Republic, and Canada. The company is on a mission to unlock the capital that fuels small businesses across America. Recognized as a Best Place to Work by Built In Boston and certified as a Great Place To Work®, Forward is investing in its employees, technology, and customer experience – with long-term success in mind every step of the way. The Analytics Engineering team at Forward plays a central role in our Data ecosystem, working with various technical stakeholders to convert raw data into actionable insights. Our team builds and optimizes data infrastructure, transforms complex data sets, and develops data pipelines that support business intelligence, advanced analytics, and predictive modeling. As an Analytics Engineer, you will design, construct, and maintain data models, collaborating with teams like Data Engineering, Data Science, DevOps, and Business Intelligence. You will help manage our modern analytics platform, using tools such as dbt, Fivetran, Snowflake, Census, and Tableau, ensuring the delivery of high-quality data products that drive innovation and informed decision-making across the organization.

Requirements

2+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence
1+ years of hands-on experience developing and maintaining production-level data transformation pipelines using dbt or equivalent scripting experience in Python
1+ years of experience with a cloud-based data warehouse such as Snowflake or Redshift
Strong proficiency in SQL and data modeling
Ability to translate complex business needs and ambiguous requirements into robust, scalable technical data solutions
Experience with business intelligence tools such as Looker, Tableau, or similar

Nice To Haves

Experience with Python

Responsibilities

Design, build, and maintain robust data models and marts using dbt, focusing on clear logic and adherence to the DRY (Don't Repeat Yourself) principle.
Collaborate with the Data Science team to prepare and transform data features used in the development and training of predictive models.
Work with the Data Engineering team to assist in deploying and ensuring the stability of data pipelines that feed production machine learning models.
Partner with the Technology teams to manage the impact of internal application schema changes and data migrations on downstream analytical models.
Assist the DevOps team in monitoring and contributing to the maintenance of our real-time streaming pipelines.
Ensure data quality and adherence to team standards by actively participating in the peer review process for other analysts' and engineers' code submissions.
Assist in the integration of new third-party data sources to enrich our existing data ecosystem.
Apply data governance standards by implementing data quality checks, documenting models in the data catalog, and following security and compliance procedures.