Company Overview:
Flipside is a commercialization engine that powers blockchain growth. We activate 110,000+ analysts to produce insights, drive narratives, and transact, building emotional connection and a strong and active community that supports token price and chain growth. We make that possible by curating best-in-class data and making that data available entirely for free. Founded in 2017, Flipside works with partners such as Solana, Near, Flow, Avalanche, SEI, Aptos, Blast, Vertex. The company is backed by leading investors including Republic Capital, True Ventures, Galaxy Digital, Collab Currency, Hashkey, M13, and more.
Job Title : Data Analyst, Finance & Product
Location : Remote
**This role will be fully remote and off-shore, international candidates are also encouraged to apply!**
Team : Internal Analytics
Job Description:
We are looking for a talented and driven Data Analyst to write and maintain data pipelines, understand our business programs using both internal data and public blockchain data, and create reports and analysis to drive data-driven decision-making across our organization.
This is a critical role on our Internal Analytics team, overseeing the programmatic delivery of internal business intelligence to our Finance and Leadership teams.
The right candidate will combine data engineering and analysis experience to own the entire reporting pipeline, from ELT through modeling, analysis, and presentation. Strong written and verbal communication skills and experience in communicating data-driven findings to a variety of stakeholders are essential for this role, which hinges on productive cross-functional collaboration to meet business goals.
Primary Responsibilities:
Data Pipelines and Modeling:
- Design, develop, and maintain robust data pipelines to support the Finance and Product team’s data needs.
- Integrate data from sources including internally-generated product data, human-collected operational data, and publicly available blockchain data into useful models and views.
- Utilize industry-standard data design patterns (Medallion Architecture) to simplify maintenance and enable adoption across the Internal Analytics team.
- Build and support business intelligence models (Star Schema) for downstream reporting and analysis.
Data Analysis and Reporting:
- Analyze financial, product, and operational data to provide actionable insights and build understanding.
- Develop and maintain dashboards and reports using SQL and Python-based data visualization tools.
- Communicate findings in written and verbal formats, both synchronously and asynchronously, as required.
Cross-Functional Collaboration and Data Integrity:
- Work closely with the Finance and Product teams to define and document their requirements, and deliver solutions that meet their needs.
- Ensure organization-wide visibility into business intelligence work with clear and consistent communication, employing basic project management skills to ensure timely delivery of commitments.
- Build a deep understanding of our business systems and data pipelines to investigate anomalous or interesting data, and ensure quality and intelligibility of downstream reporting.
Qualifications:
- Bachelor’s degree in Analytics, Data Science, Finance, Computer Science, or related technical field, or equivalent practical experience.
- 2+ years of experience in data engineering, data analysis, business intelligence, or a similar role.
- Proficiency in SQL (experience in any dialect is acceptable, though we use Snowflake SQL).
- Experience with ELT tools and data pipeline frameworks.
- Experience with data warehouse/lakehouse architectures for business intelligence.
- Strong analytical skills with the ability to integrate and interpret complex data sets.
- Excellent communication skills and the ability to work collaboratively with cross-functional teams.
Preferred Qualifications:
- Experience with data visualization tools such as Tableau, Looker, Superset, Mode, Preset, Abacum or similar.
- Knowledge of and demonstrated interest in blockchain and cryptocurrency markets.
- Familiarity with dbt, Airflow, or other data transformation and pipelining tools.
- Familiarity with financial modeling techniques.
Finance Business Intelligence (BI) Looker Data Analyst Tableau SQL data-warehouse Python Airflow apache-superset ELT DBT