Build and maintain scalable data pipelines, models, and BI dashboards that turn complex data into trusted metrics and insights. Partner with cross-functional teams to drive data-informed decisions at a Series C fintech serving small businesses. Requires 1-3 years experience, strong SQL, Python, and BI tool skills.
180k – 220k/yr
Hybrid1+ YOEData Analytics
About the role
What You’ll Be Doing
Build and maintain scalable data pipelines that power analytics data models and trusted datasets.
Write efficient SQL to transform, validate, and optimize data for analytics and reporting.
Leverage AI tools to accelerate development, improve productivity, and streamline analytics workflows.
Develop and maintain dashboards, reports, and self-service analytics for business stakeholders.
Partner with Product, Engineering, Finance, Risk, and Operations to understand data needs and deliver data-driven solutions.
Monitor data quality, investigate discrepancies, and improve the reliability of our data.
Contribute to the continuous improvement of Parafin's analytics infrastructure and analytics engineering practices.
What We’re Searching For
1–3 years of experience in Analytics Engineering, Data Analytics, Business Intelligence, Data Engineering, or a similar role.
Strong SQL skills.
Experience working with relational databases and data warehouses.
Experience with Python or another scripting language.
Familiarity with dbt or a desire to learn modern analytics engineering tools.
Experience building dashboards in Looker, Tableau, Sigma, Mode, or similar BI tools.
Strong analytical and problem-solving skills.
Excellent communication and collaboration skills.
Bachelor's degree in Computer Science, Statistics, Engineering, Mathematics, Economics, or a related quantitative field (or equivalent experience).
We Prefer If You Have
Knowledge of data modeling and analytics engineering best practices.
Experience with Databricks, Snowflake, BigQuery, or other cloud data platforms.
Experience with Git and version control.
Familiarity with Airflow, Dagster, or other workflow orchestration tools.
Experience working with financial services, lending, payments, or product analytics data.
Experience in a startup or other fast-paced, high-growth environment.
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