Data Analyst

Are you passionate about data analytics and eager to work on large-scale projects? Fingerprint is looking for a Data Analyst to join our Identification Team. You will play a crucial role in providing high-quality tools for deep data analytics over our Identification API Product, which processes approximately 1 billion requests per month.

Responsibilities:

• Develop tools for data analytics on the Identification API Product.
• Design, build, and maintain dashboards and reports that support Customer Success and the Sales Engineering organizations
• Drive internal adoption of self-service dashboards and help teams interpret the data for decision making
• Provide insights about Identification accuracy, detect anomalies, and analyze trends in time-series data.
• Foster an engineering-focused, data-driven culture within the Fingerprint team by sharing tools and knowledge on effective data analytics approaches.
• This role includes participation in a shared on-call rotation. The schedule will be communicated in advance, and we strive to balance coverage equitably while minimizing off-hours disruptions.

Qualifications:

• Proficiency in English for clear communication within an international remote team.
• BS/MS in Computer Science or a related field, or equivalent work experience.
• 3+ years of experience in Data Analytics, Analytics Engineering,  or Data Science.
• Proficient SQL skills
• Strong foundation in statistics for designing metrics and experiments.
• Practical experience with analytical storage solutions such as Clickhouse, Snowflake, BigQuery, Redshift, Databricks, etc.
• Strong coding skills with clean, maintainable code; experience with version control (Git) and collaborative development practices
• Experience building dashboards and using data visualization tools like Apache Superset, Tableau, Metabase, Looker, etc.
• Comfortable conducting ad-hoc analysis and presenting findings to cross-functional teams
• Demonstrated experience supporting internal teams by managing and resolving data and reporting requests
• Excellent communication skills and the ability to present complex data clearly to non-technical audiences

Nice to Haves:

• Familiarity with data transformation frameworks and approaches (e.g., dbt, materialized views, data pipeline tools).
• Proficiency with the Python data analytics stack (Numpy, pandas, Jupyter, etc.).
• Understanding of fundamental ML concepts, familiarity with model evaluation metrics

Technologies:

• Our stack: Clickhouse, dbt, Apache Superset (Preset), Prefect
• Relevant technologies: Google BigQuery, Amazon Redshift, Snowflake, Apache Druid, Vertica, DataBricks, Apache Airflow, Dataform, Talend, Fivetran, Stitch, Luigi, Dagster, Tableau, Power BI, Looker, Metabase, Redash