Data Analytics Engineer

We are seeking a proactive and detail-oriented Analytics Engineer to join our Data Product organization. Reporting to the Director of Data Product, this individual will play a crucial role in ensuring data integrity, developing insightful dashboards, and identifying opportunities for data enhancement. You will proactively monitor data health, identify anomalies, and develop ideas for data validation to improve data quality. You will also create insightful dashboards and reports that inform both our team and our customers about data coverage (e.g. companies of a certain size & industry by region) and user engagement (e.g. record view & list-building trends). This role is critical in ensuring our data remains fresh, comprehensive, and reliable, directly impacting the value we deliver to PE/VC/IB/CorpDev clients. This role has an opportunity to grow into advanced analytics leadership, data science, and machine learning. 

Note: this role is open to remote candidates within the US.

Responsibilities: 

• Data quality monitoring, investigation, anomaly detection: Identify and prioritize data anomalies, collaborating with Engineering to implement bulk corrections and validation mechanisms. 
• Coverage analysis & reporting: 
• Develop and maintain coverage queries and views to assess data statistics and help with Go-to-market team requests 
• Detect coverage or freshness gaps in data, recommending areas for improvement and refresh. 
• User record viewing & interaction analysis & reporting: Analyze user interaction trends to determine engagement levels with various data records, identify trending behaviors by firm type, sector, and geography, and hypothesize data coverage and freshness interventions based on those trends 
• Process Improvement: Document and automate routine analyses where possible (e.g. script a weekly report on key data quality metrics or set up alerts when certain data conditions, such as an unusual drop in record counts, occur). Continuously improve our internal data assurance processes to be more efficient and robust 
• Ad-hoc Data Requests: timely and accurately fulfill data requests while continuously exploring methods to semi or fully automate future requests (e.g. democratize data through self-serve tools and educate users) 

Qualifications: 

• Bachelor's degree required. 
• 2+ years of experience as a Data Analyst, Data Engineer, BI Analyst, or similar role 
• Proficiency in SQL (advanced level) and Python (intermediate level) with experience handling ad-hoc data queries in a fast-paced environment  
• Strong understanding of data modeling, database design, and cloud data warehouses such as Snowflake and Redshift  
• Hands-on experience with BI tools such as Kibana, Power BI, or similar platform 
• Strong analytical skills, problem-solving mindset, and attention to detail with a sense of curiosity to challenge the status quo  
• High-level understanding of metrics important to business health and basic concepts of Corporate Finance and Sales 
• Excellent communication skills and the ability to work independently 
• Nice to have, but not required: 
  • Experience in a SaaS, data provider, or finance space 
  • Exposure to private company data / financial data 
  • Knowledge of machine learning, advanced analytics, and statistical analysis 

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