Data Analyst

Industry: Finance
Remote
Company size: 251-10K
Full-time/Part-time

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Job description

A US-based company providing capital to real estate investors to fund deals, loans, and mortgage financing remedies is looking for a Data Analyst. The selected candidate will work closely with the engineering team to understand and represent the data team. The company is utilizing technology to provide new funding solutions that will fundamentally change the real estate industry. This is an exciting opportunity for developers who enjoy working in a fast-paced environment while applying their problem-solving and analytical skills.

 

Job Responsibilities:

  • Understand and document data product requirements in collaboration with Product Managers, data analysts, and data scientists
  • Use data discovery to understand the current data landscape and document the details
  • Work with business stakeholders to refine and respond to ad hoc requests and improve existing reporting and dashboards
  • Work with product and engineering teams to understand the application data model and represent the data team on the impact of any changes on downstream analytics
  • Transform various raw data sets (the application database, third-party data sets, and logs) to an analytics-friendly data structure (likely in SQL)
  • Record relevant technical and business metadata, as well as project summaries
  • Serve as a data steward to monitor and improve the data quality

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 4+ years of relevant experience working as a data analyst
  • Expertise in SQL and comfortable working with large, complex data sets
  • Proven ability to work collaboratively with technical and non-technical colleagues in various business functions at all levels
  • Hands-on experience constructing visual analytics with Tableau or Looker
  • Working knowledge of an analytics data warehouse like Snowflake, Redshift, and BigQuery
  • Familiarity with different data models 
  • Knowledge of the fundamentals of statistics and probability
  • Familiarity with fundamentals of data pipelines
  • Knowledge of Agile and test-driven methodologies
  • Strong verbal and written English communication skills
  • Strong analytical skills and passion for answering questions with data

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